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ORCIDBalaraman Ravindran
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- affiliation: Indian Institute of Technology Madras
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2020 – today
- 2025
[i97]Ambreesh Parthasarathy, Chandrasekar Subramanian, Ganesh Senrayan, Shreyash Adappanavar, Aparna Taneja, Balaraman Ravindran, Milind Tambe:
Multilinguality in LLM-Designed Reward Functions for Restless Bandits: Effects on Task Performance and Fairness. CoRR abs/2501.13120 (2025)- [i96]Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng:
International AI Safety Report. CoRR abs/2501.17805 (2025) - 2024
- [j29]Sudarsun Santhiappan
, Jeshuren Chelladurai, Balaraman Ravindran:
TOMBoost: a topic modeling based boosting approach for learning with class imbalance. Int. J. Data Sci. Anal. 17(4): 389-409 (2024) - [c153]Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran:
MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning. AAMAS 2024: 1865-1873 - [c152]Richa Verma, Durgesh Kalwar, Harshad Khadilkar, Balaraman Ravindran:
Guiding Offline Reinforcement Learning Using a Safety Expert. COMAD/CODS 2024: 82-90 - [c151]Siddharth Nishtala, Balaraman Ravindran:
Cost-Sensitive Trees for Interpretable Reinforcement Learning. COMAD/CODS 2024: 91-99 - [c150]Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan, Hardik Meisheri, Harshad Khadilkar, Balaraman Ravindran:
A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce. COMAD/CODS 2024: 430-438 - [c149]Yogesh Tripathi, Raghav Donakanti, Sahil Girhepuje, Ishan Kavathekar, Bhaskara Hanuma Vedula, Gokul S. Krishnan, Anmol Goel, Shreya Goyal, Balaraman Ravindran, Ponnurangam Kumaraguru:
InSaAF: Incorporating Safety Through Accuracy and Fairness - Are LLMs Ready for the Indian Legal Domain? JURIX 2024: 344-351 - [c148]Sangameshwar Patil, Balaraman Ravindran:
Zero-shot Learning based Alternatives for Class Imbalanced Learning Problem in Enterprise Software Defect Analysis. MSR 2024: 140-141 - [i95]Yogesh Tripathi, Raghav Donakanti, Sahil Girhepuje, Ishan Kavathekar, Bhaskara Hanuma Vedula, Gokul S. Krishnan, Shreya Goyal, Anmol Goel, Balaraman Ravindran, Ponnurangam Kumaraguru:
InSaAF: Incorporating Safety through Accuracy and Fairness | Are LLMs ready for the Indian Legal Domain? CoRR abs/2402.10567 (2024) - [i94]Atharvan Dogra, Ameet Deshpande, John Nay, Tanmay Rajpurohit, Ashwin Kalyan, Balaraman Ravindran:
Deception in Reinforced Autonomous Agents: The Unconventional Rabbit Hat Trick in Legislation. CoRR abs/2405.04325 (2024) - [i93]Ambreesh Parthasarathy, Aditya Phalnikar, Ameen Jauhar, Dhruv Somayajula, Gokul S. Krishnan, Balaraman Ravindran:
Participatory Approaches in AI Development and Governance: A Principled Approach. CoRR abs/2407.13100 (2024) - [i92]Ambreesh Parthasarathy, Aditya Phalnikar, Gokul S. Krishnan, Ameen Jauhar, Balaraman Ravindran:
Participatory Approaches in AI Development and Governance: Case Studies. CoRR abs/2407.13103 (2024) - [i91]Sai Kiran Narayanaswami, Gopalakrishnan Srinivasan, Balaraman Ravindran:
QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities. CoRR abs/2412.00408 (2024) - 2023
- [j28]Shreya Goyal, Sumanth Doddapaneni, Mitesh M. Khapra, Balaraman Ravindran:
A Survey of Adversarial Defenses and Robustness in NLP. ACM Comput. Surv. 55(14s): 332:1-332:39 (2023) - [j27]Harsha Kokel, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli:
RePReL: a unified framework for integrating relational planning and reinforcement learning for effective abstraction in discrete and continuous domains. Neural Comput. Appl. 35(23): 16877-16892 (2023) - [j26]Tarun Kumar, Ramanathan Sethuraman, Sanga Mitra, Balaraman Ravindran, Manikandan Narayanan:
MultiCens: Multilayer network centrality measures to uncover molecular mediators of tissue-tissue communication. PLoS Comput. Biol. 19(4) (2023) - [c147]Saket Gurukar, Shaileshh Bojja Venkatakrishnan, Balaraman Ravindran, Srinivasan Parthasarathy:
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks. ASONAM 2023: 245-252 - [c146]Kushal Chauhan, Soumya Chatterjee, Akash Reddy, Aniruddha S, Balaraman Ravindran, Pradeep Shenoy:
Matching Options to Tasks using Option-Indexed Hierarchical Reinforcement Learning. AAMAS 2023: 2631-2633 - [c145]Mayuresh Kunjir, Sanjay Chawla, Siddarth Chandrasekar, Devika Jay, Balaraman Ravindran:
Optimizing Traffic Control with Model-Based Learning: A Pessimistic Approach to Data-Efficient Policy Inference. KDD 2023: 1176-1187 - [c144]Adithya Ramesh, Balaraman Ravindran:
Physics-Informed Model-Based Reinforcement Learning. L4DC 2023: 26-37 - [c143]Naganand Yadati, Tarun Kumar, Deepak Maurya, Balaraman Ravindran, Partha P. Talukdar:
HEAL: Unlocking the Potential of Learning on Hypergraphs Enriched With Attributes and Layers. LoG 2023: 34 - [c142]Tamizharasan Kanagamani, Madhuvanthi Muliya, V. Srinivasa Chakravarthy, Balaraman Ravindran, Ramshekhar N. Menon:
Oscillatory Network and Deep Value Network Based Memory Replay Model of Hippocampus. PReMI 2023: 117-127 - [i90]Sahil Girhepuje, Anmol Goel, Gokul S. Krishnan, Shreya Goyal, Satyendra Pandey, Ponnurangam Kumaraguru, Balaraman Ravindran:
Are Models Trained on Indian Legal Data Fair? CoRR abs/2303.07247 (2023) - [i89]Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran:
Bi-level Latent Variable Model for Sample-Efficient Multi-Agent Reinforcement Learning. CoRR abs/2304.06011 (2023) - [i88]Sudarsun Santhiappan, Nitin Shravan, Balaraman Ravindran:
Clustering Indices based Automatic Classification Model Selection. CoRR abs/2305.13926 (2023) - [i87]Returaj Burnwal, Anirban Santara, Nirav P. Bhatt, Balaraman Ravindran, Gaurav Aggarwal:
GAN-MPC: Training Model Predictive Controllers with Parameterized Cost Functions using Demonstrations from Non-identical Experts. CoRR abs/2305.19111 (2023) - [i86]Saket Gurukar, Shaileshh Bojja Venkatakrishnan, Balaraman Ravindran, Srinivasan Parthasarathy:
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks. CoRR abs/2306.14357 (2023) - [i85]Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan, Harshad Khadilkar, Hardik Meisheri, Balaraman Ravindran:
Multi-Agent Learning of Efficient Fulfilment and Routing Strategies in E-Commerce. CoRR abs/2311.16171 (2023) - [i84]Gokul S. Krishnan, Sarala Padi, Craig S. Greenberg, Balaraman Ravindran, Dinesh Manocha, Ram D. Sriram:
LineConGraphs: Line Conversation Graphs for Effective Emotion Recognition using Graph Neural Networks. CoRR abs/2312.03756 (2023) - 2022
- [j25]Balaraman Ravindran, Sunita Sarawagi, Aditi Jain:
AI and data science centers in top Indian academic institutions. Commun. ACM 65(11): 94-97 (2022) - [j24]Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Srinivasan Parthasarathy, Balaraman Ravindran:
Scaling Graph Propagation Kernels for Predictive Learning. Frontiers Big Data 5: 616617 (2022) - [j23]Joseph H. R. Isaac, Manivannan Muniyandi, Balaraman Ravindran:
Single Shot Corrective CNN for Anatomically Correct 3D Hand Pose Estimation. Frontiers Artif. Intell. 5: 759255 (2022) - [j22]Hardik Meisheri, Nazneen N. Sultana, Mayank Baranwal, Vinita Baniwal, Somjit Nath, Satyam Verma, Balaraman Ravindran, Harshad Khadilkar:
Scalable multi-product inventory control with lead time constraints using reinforcement learning. Neural Comput. Appl. 34(3): 1735-1757 (2022) - [j21]Saket Gurukar, Priyesh Vijayan, Srinivasan Parthasarathy, Balaraman Ravindran, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel:
Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress. Trans. Mach. Learn. Res. 2022 (2022) - [c141]Rishi Saket, Aravindan Raghuveer, Balaraman Ravindran:
On Combining Bags to Better Learn from Label Proportions. AISTATS 2022: 5913-5927 - [c140]Jay Nandy, Rishi Saket, Prateek Jain, Jatin Chauhan, Balaraman Ravindran, Aravindan Raghuveer:
Domain-Agnostic Contrastive Representations for Learning from Label Proportions. CIKM 2022: 1542-1551 - [c139]Pranshu Malviya, Balaraman Ravindran, Sarath Chandar:
TAG: Task-based Accumulated Gradients for Lifelong learning. CoLLAs 2022: 366-389 - [c138]Sai Kiran Narayanaswami, Nandan Sudarsanam, Balaraman Ravindran:
An Active Learning Framework for Efficient Robust Policy Search. COMAD/CODS 2022: 1-9 - [c137]Sapana Chaudhary, Balaraman Ravindran:
Smooth Imitation Learning via Smooth Costs and Smooth Policies. COMAD/CODS 2022: 63-71 - [c136]Sruthikeerthi Nandita, Goutham Zampani, Gokul S. Krishnan, Gitakrishnan Ramadurai, Balaraman Ravindran:
Automated Incident Location Identification for EMS from Ambulance Geospatial Data. COMAD/CODS 2022: 162-168 - [c135]Manoj Bharadhwaj, Gitakrishnan Ramadurai, Balaraman Ravindran:
Detecting Vehicles on the Edge: Knowledge Distillation to Improve Performance in Heterogeneous Road Traffic. CVPR Workshops 2022: 3191-3197 - [c134]Harsha Kokel, Nikhilesh Prabhakar, Balaraman Ravindran, Erik Blasch, Prasad Tadepalli, Sriraam Natarajan:
Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion. FUSION 2022: 1-8 - [c133]Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran:
Revisiting Link Prediction on Heterogeneous Graphs with a Multi-view Perspective. ICDM 2022: 358-367 - [c132]Chandrasekar Subramanian, Balaraman Ravindran:
Causal Contextual Bandits with Targeted Interventions. ICLR 2022 - [c131]Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran:
Evolutionary Approach to Security Games with Signaling. IJCAI 2022: 620-627 - [c130]Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran:
Multi-Variate Time Series Forecasting on Variable Subsets. KDD 2022: 76-86 - [i83]Shreya Goyal, Sumanth Doddapaneni, Mitesh M. Khapra, Balaraman Ravindran:
A Survey in Adversarial Defences and Robustness in NLP. CoRR abs/2203.06414 (2022) - [i82]Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran:
Evolutionary Approach to Security Games with Signaling. CoRR abs/2204.14173 (2022) - [i81]Kushal Chauhan, Soumya Chatterjee, Akash Reddy, Balaraman Ravindran, Pradeep Shenoy:
Matching options to tasks using Option-Indexed Hierarchical Reinforcement Learning. CoRR abs/2206.05750 (2022) - [i80]Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran:
Multi-Variate Time Series Forecasting on Variable Subsets. CoRR abs/2206.12626 (2022) - [i79]Jeshuren Chelladurai, Sudarsun Santhiappan, Balaraman Ravindran:
GrabQC: Graph based Query Contextualization for automated ICD coding. CoRR abs/2207.06802 (2022) - [i78]Neeraja Kirtane, Jeshuren Chelladurai, Balaraman Ravindran, Ashish V. Tendulkar:
ReGrAt: Regularization in Graphs using Attention to handle class imbalance. CoRR abs/2211.14770 (2022) - [i77]Adithya Ramesh, Balaraman Ravindran:
Physics-Informed Model-Based Reinforcement Learning. CoRR abs/2212.02179 (2022) - 2021
- [j20]Joseph Hosanna Raj Isaac, Manivannan Muniyandi, Balaraman Ravindran:
Corrective Filter Based on Kinematics of Human Hand for Pose Estimation. Frontiers Virtual Real. 2: 663618 (2021) - [j19]Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, Balaraman Ravindran:
MADRaS : Multi Agent Driving Simulator. J. Artif. Intell. Res. 70: 1517-1555 (2021) - [c129]Daksh Anand, Vaibhav Gupta, Praveen Paruchuri, Balaraman Ravindran:
An Enhanced Advising Model in Teacher-Student Framework using State Categorization. AAAI 2021: 6653-6660 - [c128]Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran:
Relational Boosted Bandits. AAAI 2021: 12123-12130 - [c127]Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran:
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal. ACML 2021: 518-533 - [c126]Rajan Kumar Soni, Karthick Seshadri, Balaraman Ravindran:
Metric Learning for comparison of HMMs using Graph Neural Networks. ACML 2021: 1365-1380 - [c125]Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli:
RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction. ICAPS 2021: 533-541 - [c124]Karthik Visweswariah, Beethika Tripathi, Mitesh M. Khapra, Balaraman Ravindran:
A Joint Training Framework for Open-World Knowledge Graph Embeddings. AKBC 2021 - [c123]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
SEERL: Sample Efficient Ensemble Reinforcement Learning. AAMAS 2021: 1100-1108 - [c122]Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe:
Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. AAMAS 2021: 1353-1361 - [c121]Sudarsun Santhiappan, Balaraman Ravindran:
A semi-supervised approach to growing classification trees. COMAD/CODS 2021: 29-37 - [c120]Vaishnavi Muralidharan, Nandan Sudarsanam, Balaraman Ravindran:
Inferring customer occupancy status in for-hire vehicles using PU Learning. COMAD/CODS 2021: 290-298 - [c119]Sudarsun Santhiappan, Nitin Shravan, Balaraman Ravindran:
Is it hard to learn a classifier on this dataset? COMAD/CODS 2021: 299-306 - [c118]Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran:
Semi-Supervised Deep Learning for Multiplex Networks. KDD 2021: 1234-1244 - [c117]Jeshuren Chelladurai, Sudarsun Santhiappan, Balaraman Ravindran:
GrabQC: Graph Based Query Contextualization for Automated ICD Coding. PAKDD (1) 2021: 225-237 - [i76]Jahnvi Patel, Devika Jay, Balaraman Ravindran, K. Shanti Swarup:
Neural Fitted Q Iteration based Optimal Bidding Strategy in Real Time Reactive Power Market_1. CoRR abs/2101.02456 (2021) - [i75]Nahas Pareekutty, Francis James, Balaraman Ravindran, Suril Vijaykumar Shah:
qRRT: Quality-Biased Incremental RRT for Optimal Motion Planning in Non-Holonomic Systems. CoRR abs/2101.02635 (2021) - [i74]Deepak Maurya, Balaraman Ravindran:
Hyperedge Prediction using Tensor Eigenvalue Decomposition. CoRR abs/2102.04986 (2021) - [i73]Siddharth Nishtala, Lovish Madaan, Aditya Mate, Harshavardhan Kamarthi, Anirudh Grama, Divy Thakkar, Dhyanesh Narayanan, Suresh Chaudhary, Neha Madhiwalla, Ramesh Padmanabhan, Aparna Hegde, Pradeep Varakantham, Balaraman Ravindran, Milind Tambe:
Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes. CoRR abs/2103.09052 (2021) - [i72]Pranshu Malviya, Balaraman Ravindran, Sarath Chandar:
TAG: Task-based Accumulated Gradients for Lifelong learning. CoRR abs/2105.05155 (2021) - [i71]Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran:
Semi-Supervised Deep Learning for Multiplex Networks. CoRR abs/2110.02038 (2021) - [i70]Amrit Diggavi Seshadri, Balaraman Ravindran:
Multi-Tailed, Multi-Headed, Spatial Dynamic Memory refined Text-to-Image Synthesis. CoRR abs/2110.08143 (2021) - [i69]Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli:
Dynamic probabilistic logic models for effective abstractions in RL. CoRR abs/2110.08318 (2021) - [i68]Sapana Chaudhary, Balaraman Ravindran:
Smooth Imitation Learning via Smooth Costs and Smooth Policies. CoRR abs/2111.02354 (2021) - [i67]Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran:
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal. CoRR abs/2111.14348 (2021) - 2020
- [j18]Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran:
Hypergraph clustering by iteratively reweighted modularity maximization. Appl. Netw. Sci. 5(1): 52 (2020) - [j17]Sangameshwar Patil, Balaraman Ravindran:
Predicting software defect type using concept-based classification. Empir. Softw. Eng. 25(2): 1341-1378 (2020) - [j16]Abhishek Ghose, Balaraman Ravindran:
Interpretability With Accurate Small Models. Frontiers Artif. Intell. 3: 3 (2020) - [j15]Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran:
Rate of change analysis for interestingness measures. Knowl. Inf. Syst. 62(1): 239-258 (2020) - [j14]Sanjay Ganapathy, Swagath Venkataramani, Giridhur Sriraman, Balaraman Ravindran, Anand Raghunathan:
DyVEDeep: Dynamic Variable Effort Deep Neural Networks. ACM Trans. Embed. Comput. Syst. 19(3): 16:1-16:24 (2020) - [c116]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract). AAAI 2020: 13905-13906 - [c115]Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Towards Transparent and Explainable Attention Models. ACL 2020: 4206-4216 - [c114]Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe:
Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. AAMAS 2020: 575-583 - [c113]Anirban Santara, Rishabh Madan, Pabitra Mitra, Balaraman Ravindran:
ExTra: Transfer-guided Exploration. AAMAS 2020: 1987-1989 - [c112]Siddharth Nayak, Balaraman Ravindran:
Reinforcement Learning for Improving Object Detection. ECCV Workshops (5) 2020: 149-161 - [c111]Sanchari Sen, Balaraman Ravindran, Anand Raghunathan:
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks. ICLR 2020 - [c110]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Understanding Dynamic Scenes using Graph Convolution Networks. IROS 2020: 8279-8286 - [c109]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks. IV 2020: 321-327 - [c108]Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran:
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning. ECML/PKDD (2) 2020: 509-524 - [c107]Anasua Mitra, Priyesh Vijayan, Srinivasan Parthasarathy, Balaraman Ravindran:
A Unified Non-Negative Matrix Factorization Framework for Semi Supervised Learning on Graphs. SDM 2020: 487-495 - [c106]Tarun Kumar, K. Darwin, Srinivasan Parthasarathy, Balaraman Ravindran:
HPRA: Hyperedge Prediction using Resource Allocation. WebSci 2020: 135-143 - [i66]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
SEERL: Sample Efficient Ensemble Reinforcement Learning. CoRR abs/2001.05209 (2020) - [i65]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks. CoRR abs/2002.00786 (2020) - [i64]Sanchari Sen, Balaraman Ravindran, Anand Raghunathan:
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks. CoRR abs/2004.10162 (2020) - [i63]Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Towards Transparent and Explainable Attention Models. CoRR abs/2004.14243 (2020) - [i62]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Understanding Dynamic Scenes using Graph Convolution Networks. CoRR abs/2005.04437 (2020) - [i61]Nikita Moghe, Priyesh Vijayan, Balaraman Ravindran, Mitesh M. Khapra:
On Incorporating Structural Information to improve Dialogue Response Generation. CoRR abs/2005.14315 (2020) - [i60]Nazneen N. Sultana, Hardik Meisheri, Vinita Baniwal, Somjit Nath, Balaraman Ravindran, Harshad Khadilkar:
Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains. CoRR abs/2006.04037 (2020) - [i59]Siddharth Nishtala, Harshavardhan Kamarthi, Divy Thakkar, Dhyanesh Narayanan, Anirudh Grama, Ramesh Padmanabhan, Neha Madhiwalla, Suresh Chaudhary, Balaraman Ravindran, Milind Tambe:
Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement. CoRR abs/2006.07590 (2020) - [i58]Tarun Kumar, K. Darwin, Srinivasan Parthasarathy, Balaraman Ravindran:
HPRA: Hyperedge Prediction using Resource Allocation. CoRR abs/2006.11070 (2020) - [i57]Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran:
A Causal Linear Model to Quantify Edge Unfairness for Unfair Edge Prioritization and Discrimination Removal. CoRR abs/2007.05516 (2020) - [i56]Siddharth Nayak, Balaraman Ravindran:
Reinforcement Learning for Improving Object Detection. CoRR abs/2008.08005 (2020) - [i55]Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, Balaraman Ravindran:
MADRaS : Multi Agent Driving Simulator. CoRR abs/2010.00993 (2020) - [i54]Anand A. Rajasekar, Karthik Raman, Balaraman Ravindran:
Goal directed molecule generation using Monte Carlo Tree Search. CoRR abs/2010.16399 (2020) - [i53]Deepak Maurya, Balaraman Ravindran:
Hypergraph Partitioning using Tensor Eigenvalue Decomposition. CoRR abs/2011.07683 (2020) - [i52]Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran:
Relational Boosted Bandits. CoRR abs/2012.09220 (2020) - [i51]Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe:
Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. CoRR abs/2012.10389 (2020)
2010 – 2019
- 2019
- [j13]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Studying the plasticity in deep convolutional neural networks using random pruning. Mach. Vis. Appl. 30(2): 203-216 (2019) - [c105]Manan Tomar, Akhil Sathuluri, Balaraman Ravindran:
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. AAAI 2019: 10053-10054 - [c104]Sai Kiran Narayanaswami, Balaraman Ravindran, Venkatesh Ramaiyan:
Generalized random Surfer-Pair models. ASONAM 2019: 452-455 - [c103]Vaibhav Gupta, Daksh Anand, Praveen Paruchuri, Balaraman Ravindran:
Advice Replay Approach for Richer Knowledge Transfer in Teacher Student Framework. AAMAS 2019: 1997-1999 - [c102]Manan Tomar, Akhil Sathuluri, Balaraman Ravindran:
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. AAMAS 2019: 2226-2228 - [c101]Athindran Ramesh Kumar, Balaraman Ravindran, Anand Raghunathan:
Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing. COMAD/CODS 2019: 150-156 - [c100]Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran:
A New Measure of Modularity in Hypergraphs: Theoretical Insights and Implications for Effective Clustering. COMPLEX NETWORKS (1) 2019: 286-297 - [c99]Manju Manohar Manjalavil, Gitakrishnan Ramadurai, Balaraman Ravindran:
Temporal Analysis of a Bus Transit Network. COMPLEX NETWORKS (2) 2019: 944-954 - [c98]Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Let's Ask Again: Refine Network for Automatic Question Generation. EMNLP/IJCNLP (1) 2019: 3312-3321 - [c97]Rahul Ramesh, Manan Tomar, Balaraman Ravindran:
Successor Options: An Option Discovery Framework for Reinforcement Learning. IJCAI 2019: 3304-3310 - [c96]Revanth Reddy, Sarath Chandar, Balaraman Ravindran:
Edge Replacement Grammars : A Formal Language Approach for Generating Graphs. SDM 2019: 351-359 - [i50]Sai Kiran Narayanaswami, Nandan Sudarsanam, Balaraman Ravindran:
An Active Learning Framework for Efficient Robust Policy Search. CoRR abs/1901.00117 (2019) - [i49]Harish Kumar, Balaraman Ravindran:
Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning. CoRR abs/1902.01973 (2019) - [i48]Revanth Reddy, Sarath Chandar, Balaraman Ravindran:
Edge Replacement Grammars: A Formal Language Approach for Generating Graphs. CoRR abs/1902.07159 (2019) - [i47]Saket Gurukar, Priyesh Vijayan, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, Balaraman Ravindran, Srinivasan Parthasarathy:
Network Representation Learning: Consolidation and Renewed Bearing. CoRR abs/1905.00987 (2019) - [i46]Abhishek Ghose, Balaraman Ravindran:
Optimal Resampling for Learning Small Models. CoRR abs/1905.01520 (2019) - [i45]Rahul Ramesh, Manan Tomar, Balaraman Ravindran:
Successor Options: An Option Discovery Framework for Reinforcement Learning. CoRR abs/1905.05731 (2019) - [i44]Manan Tomar, Akhil Sathuluri, Balaraman Ravindran:
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. CoRR abs/1905.07193 (2019) - [i43]Abhishek Ghose, Balaraman Ravindran:
Learning Interpretable Models Using an Oracle. CoRR abs/1906.06852 (2019) - [i42]Anirban Santara, Rishabh Madan, Balaraman Ravindran, Pabitra Mitra:
ExTra: Transfer-guided Exploration. CoRR abs/1906.11785 (2019) - [i41]Sai Kiran Narayanaswami, Balaraman Ravindran, Venkatesh Ramaiyan:
Generalized Random Surfer-Pair Models. CoRR abs/1907.01420 (2019) - [i40]Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe:
Learning policies for Social network discovery with Reinforcement learning. CoRR abs/1907.11625 (2019) - [i39]Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran:
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning. CoRR abs/1909.04134 (2019) - [i38]Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Let's Ask Again: Refine Network for Automatic Question Generation. CoRR abs/1909.05355 (2019) - [i37]Hardik Meisheri, Vinita Baniwal, Nazneen N. Sultana, Balaraman Ravindran, Harshad Khadilkar:
Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems. CoRR abs/1910.00211 (2019) - 2018
- [j12]Nandan Sudarsanam, Balaraman Ravindran:
Using Linear Stochastic Bandits to extend traditional offline Designed Experiments to online settings. Comput. Ind. Eng. 115: 471-485 (2018) - [j11]Dibu John Philip, Nandan Sudarsanam, Balaraman Ravindran:
Improved Insights on Financial Health through Partially Constrained Hidden Markov Model Clustering on Loan Repayment Data. Data Base 49(3): 98-113 (2018) - [c95]Subhojyoti Mukherjee, K. P. Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Efficient-UCBV: An Almost Optimal Algorithm Using Variance Estimates. AAAI 2018: 6417-6424 - [c94]Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
RAIL: Risk-Averse Imitation Learning. AAMAS 2018: 2062-2063 - [c93]Sudarsun Santhiappan, Jeshuren Chelladurai, Balaraman Ravindran:
A novel topic modeling based weighting framework for class imbalance learning. COMAD/CODS 2018: 20-29 - [c92]Chandramohan T. N, Balaraman Ravindran:
A neural attention based approach for clickstream mining. COMAD/CODS 2018: 118-127 - [c91]Deepak Mittal, Avinash Reddy, Gitakrishnan Ramadurai, Kaushik Mitra, Balaraman Ravindran:
Training a deep learning architecture for vehicle detection using limited heterogeneous traffic data. COMSNETS 2018: 589-294 - [c90]Dibu John Philip, Nandan Sudarsanam, Balaraman Ravindran:
A Partial Parameter HMM Based Clustering on Loan Repayment Data: Insights into Financial Behavior and Intent to Repay. HICSS 2018: 1-10 - [c89]Balaraman Ravindran:
Looking Under the Hood of Deep Neural Networks. HiPC 2018: 1 - [c88]Sahil Sharma, Ashutosh Kumar Jha, Parikshit Hegde, Balaraman Ravindran:
Learning to Multi-Task by Active Sampling. ICLR (Poster) 2018 - [c87]Vignesh Prasad, Karmesh Yadav, Rohitashva Singh Saurabh, Swapnil Daga, Nahas Pareekutty, K. Madhava Krishna, Balaraman Ravindran, Brojeshwar Bhowmick:
Learning to Prevent Monocular SLAM Failure using Reinforcement Learning. ICVGIP 2018: 47:1-47:9 - [c86]Meha Kaushik, Vignesh Prasad, K. Madhava Krishna, Balaraman Ravindran:
Overtaking Maneuvers in Simulated Highway Driving using Deep Reinforcement Learning. Intelligent Vehicles Symposium 2018: 1885-1890 - [c85]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks. WACV 2018: 848-857 - [i36]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks. CoRR abs/1801.10447 (2018) - [i35]Parijat Dewangan, S. Phani Teja, K. Madhava Krishna, Abhishek Sarkar, Balaraman Ravindran:
DiGrad: Multi-Task Reinforcement Learning with Shared Actions. CoRR abs/1802.10463 (2018) - [i34]Ghulam Ahmed Ansari, Sagar J. P, Sarath Chandar, Balaraman Ravindran:
Language Expansion In Text-Based Games. CoRR abs/1805.07274 (2018) - [i33]Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Balaraman Ravindran:
HOPF: Higher Order Propagation Framework for Deep Collective Classification. CoRR abs/1805.12421 (2018) - [i32]Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Balaraman Ravindran:
Fusion Graph Convolutional Networks. CoRR abs/1805.12528 (2018) - [i31]Athindran Ramesh Kumar, Balaraman Ravindran, Anand Raghunathan:
Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing. CoRR abs/1809.01701 (2018) - [i30]Ameet Deshpande, Harshavardhan P. K, Balaraman Ravindran:
Discovering hierarchies using Imitation Learning from hierarchy aware policies. CoRR abs/1812.00225 (2018) - [i29]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning. CoRR abs/1812.10240 (2018) - [i28]Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran:
Hypergraph Clustering: A Modularity Maximization Approach. CoRR abs/1812.10869 (2018) - 2017
- [c84]Aravind S. Lakshminarayanan, Sahil Sharma, Balaraman Ravindran:
Dynamic Action Repetition for Deep Reinforcement Learning. AAAI 2017: 2133-2139 - [c83]Preksha Nema, Mitesh M. Khapra, Anirban Laha, Balaraman Ravindran:
Diversity driven attention model for query-based abstractive summarization. ACL (1) 2017: 1063-1072 - [c82]Prathamesh Deshpande, Balaraman Ravindran:
MCEIL: An Improved Scoring Function for Overlapping Community Detection using Seed Expansion Methods. ASONAM 2017: 652-659 - [c81]Vignesh Prasad, Rishabh Jangir, Balaraman Ravindran, K. Madhava Krishna:
Data Driven Strategies for Active Monocular SLAM using Inverse Reinforcement Learning. AAMAS 2017: 1697-1699 - [c80]Akash Jain, Rupesh Nasre, Balaraman Ravindran:
DCEIL: Distributed Community Detection with the CEIL Score. HPCC/SmartCity/DSS 2017: 146-153 - [c79]Pratik Vinay Gupte, Balaraman Ravindran, Srinivasan Parthasarathy:
Role Discovery in Graphs Using Global Features: Algorithms, Applications and a Novel Evaluation Strategy. ICDE 2017: 771-782 - [c78]Janarthanan Rajendran, Aravind S. Lakshminarayanan, Mitesh M. Khapra, P. Prasanna, Balaraman Ravindran:
Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain. ICLR (Poster) 2017 - [c77]Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran, Sergey Levine:
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. ICLR (Poster) 2017 - [c76]Sahil Sharma, Aravind S. Lakshminarayanan, Balaraman Ravindran:
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning. ICLR (Poster) 2017 - [c75]Sahil Sharma, Balaraman Ravindran:
Online Multi-Task Learning Using Active Sampling. ICLR (Workshop) 2017 - [c74]Subhojyoti Mukherjee, Kolar Purushothama Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Thresholding Bandits with Augmented UCB. IJCAI 2017: 2515-2521 - [c73]Girraj Pahariya, Balaraman Ravindran, Sukhendu Das:
Dynamic Class Learning Approach for Smart CBIR. NCVPRIPG 2017: 327-337 - [i27]Sahil Sharma, Balaraman Ravindran:
Online Multi-Task Learning Using Active Sampling. CoRR abs/1702.06053 (2017) - [i26]Sahil Sharma, Aravind S. Lakshminarayanan, Balaraman Ravindran:
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning. CoRR abs/1702.06054 (2017) - [i25]Sanjay Ganapathy, Swagath Venkataramani, Balaraman Ravindran, Anand Raghunathan:
DyVEDeep: Dynamic Variable Effort Deep Neural Networks. CoRR abs/1704.01137 (2017) - [i24]Subhojyoti Mukherjee, Kolar Purushothama Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Thresholding Bandits with Augmented UCB. CoRR abs/1704.02281 (2017) - [i23]Preksha Nema, Mitesh M. Khapra, Anirban Laha, Balaraman Ravindran:
Diversity driven Attention Model for Query-based Abstractive Summarization. CoRR abs/1704.08300 (2017) - [i22]Sahil Sharma, Aravind Suresh, Rahul Ramesh, Balaraman Ravindran:
Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning. CoRR abs/1705.07269 (2017) - [i21]Sahil Sharma, Girish Raguvir J, Srivatsan Ramesh, Balaraman Ravindran:
Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement Learning. CoRR abs/1705.07445 (2017) - [i20]Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
RAIL: Risk-Averse Imitation Learning. CoRR abs/1707.06658 (2017) - [i19]Rakesh R. Menon, Balaraman Ravindran:
Shared Learning : Enhancing Reinforcement in $Q$-Ensembles. CoRR abs/1709.04909 (2017) - [i18]Subhojyoti Mukherjee, K. P. Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Efficient-UCBV: An Almost Optimal Algorithm using Variance Estimates. CoRR abs/1711.03591 (2017) - [i17]Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran:
Rate of Change Analysis for Interestingness Measures. CoRR abs/1712.05193 (2017) - 2016
- [j10]Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran:
Correlational Neural Networks. Neural Comput. 28(2): 257-285 (2016) - [c72]Varun Gangal, Abhishek Narwekar, Balaraman Ravindran, Ramasuri Narayanam:
Trust and Distrust Across Coalitions: Shapley Value Based Centrality Measures for Signed Networks (Student Abstract Version). AAAI 2016: 4212- - [c71]Varun Gangal, Balaraman Ravindran, Ramasuri Narayanam:
HEMI: Hyperedge Majority Influence Maximization. SocInf@IJCAI 2016: 38-47 - [c70]Janarthanan Rajendran, Mitesh M. Khapra, Sarath Chandar, Balaraman Ravindran:
Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning. HLT-NAACL 2016: 171-181 - [e4]Amol Deshpande, Balaraman Ravindran, Sayan Ranu:
21st International Conference on Management of Data, COMAD 2016, Pune, India, March 11-13, 2016. Computer Society of India 2016 [contents] - [i16]Nandan Sudarsanam, Balaraman Ravindran:
Linear Bandit algorithms using the Bootstrap. CoRR abs/1605.01185 (2016) - [i15]Ramnandan Krishnamurthy, Aravind S. Lakshminarayanan, Peeyush Kumar, Balaraman Ravindran:
Hierarchical Reinforcement Learning using Spatio-Temporal Abstractions and Deep Neural Networks. CoRR abs/1605.05359 (2016) - [i14]Aravind S. Lakshminarayanan, Sahil Sharma, Balaraman Ravindran:
Dynamic Frame skip Deep Q Network. CoRR abs/1605.05365 (2016) - [i13]Varun Gangal, Balaraman Ravindran, Ramasuri Narayanam:
HEMI: Hyperedge Majority Influence Maximization. CoRR abs/1606.05065 (2016) - [i12]Vignesh Prasad, Saurabh Singh, Nahas Pareekutty, Balaraman Ravindran, K. Madhava Krishna:
SLAM-Safe Planner: Preventing Monocular SLAM Failure using Reinforcement Learning. CoRR abs/1607.07558 (2016) - [i11]Aravind Rajeswaran, Sarvjeet Ghotra, Sergey Levine, Balaraman Ravindran:
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. CoRR abs/1610.01283 (2016) - [i10]Sai Praveen Bangaru, J. S. Suhas, Balaraman Ravindran:
Exploration for Multi-task Reinforcement Learning with Deep Generative Models. CoRR abs/1611.09894 (2016) - 2015
- [j9]Pragathi Priyadharsini Balasubramani, V. Srinivasa Chakravarthy, Balaraman Ravindran, Ahmed A. Moustafa:
A network model of basal ganglia for understanding the roles of dopamine and serotonin in reward-punishment-risk based decision making. Frontiers Comput. Neurosci. 9: 76 (2015) - [j8]K. S. Gayathri, Susan Elias, Balaraman Ravindran:
Hierarchical activity recognition for dementia care using Markov Logic Network. Pers. Ubiquitous Comput. 19(2): 271-285 (2015) - [c69]Ramakumar Pasumarthi, Ramasuri Narayanam, Balaraman Ravindran:
Near Optimal Strategies for Targeted Marketing in Social Networks. AAMAS 2015: 1679-1680 - [c68]Sangameshwar Patil, Balaraman Ravindran:
Active Learning Based Weak Supervision for Textual Survey Response Classification. CICLing (2) 2015: 309-320 - [c67]Sanjukta Roy, Balaraman Ravindran:
Measuring network centrality using hypergraphs. CODS 2015: 59-68 - [c66]Subendhu Rongali, A. P. Sarath Chandar, Balaraman Ravindran:
From multiple views to single view: a neural network approach. CODS 2015: 104-109 - [c65]Avijit Saha, Ayan Acharya, Balaraman Ravindran, Joydeep Ghosh:
Nonparametric Poisson Factorization Machine. ICDM 2015: 967-972 - [c64]Vishnu Sankar, Balaraman Ravindran, S. Shivashankar:
CEIL: A Scalable, Resolution Limit Free Approach for Detecting Communities in Large Networks. IJCAI 2015: 2097-2103 - [c63]Sai Nageswar Satchidanand, Harini Ananthapadmanaban, Balaraman Ravindran:
Extended Discriminative Random Walk: A Hypergraph Approach to Multi-View Multi-Relational Transductive Learning. IJCAI 2015: 3791-3797 - [c62]Avijit Saha, Rishabh Misra, Balaraman Ravindran:
Scalable Bayesian Matrix Factorization. MUSE@PKDD/ECML 2015: 43-54 - [c61]Saket Gurukar, Sayan Ranu, Balaraman Ravindran:
COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks. SIGMOD Conference 2015: 475-489 - [i9]Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran:
Correlational Neural Networks. CoRR abs/1504.07225 (2015) - [i8]Abhinav Garlapati, Aditi Raghunathan, Vaishnavh Nagarajan, Balaraman Ravindran:
A Reinforcement Learning Approach to Online Learning of Decision Trees. CoRR abs/1507.06923 (2015) - [i7]P. Prasanna, Sarath Chandar, Balaraman Ravindran:
TSEB: More Efficient Thompson Sampling for Policy Learning. CoRR abs/1510.02874 (2015) - [i6]Janarthanan Rajendran, P. Prasanna, Balaraman Ravindran, Mitesh M. Khapra:
ADAAPT: A Deep Architecture for Adaptive Policy Transfer from Multiple Sources. CoRR abs/1510.02879 (2015) - [i5]Janarthanan Rajendran, Mitesh M. Khapra, Sarath Chandar, Balaraman Ravindran:
Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning. CoRR abs/1510.03519 (2015) - 2014
- [j7]Pragathi Priyadharsini Balasubramani, V. Srinivasa Chakravarthy, Balaraman Ravindran, Ahmed A. Moustafa:
An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning. Frontiers Comput. Neurosci. 8: 47 (2014) - [c60]Priyesh Vijayan, Shivashankar Subramanian, Balaraman Ravindran:
Multi-label collective classification in multi-attribute multi-relational network data. ASONAM 2014: 509-514 - [c59]Saket Gurukar, Balaraman Ravindran:
Temporal analysis of telecom call graphs. COMSNETS 2014: 1-6 - [c58]Sai Nageswar Satchidanand, Siddharth Kumar Jain, Amit Maurya, Balaraman Ravindran:
Studying Indian Railways Network using hypergraphs. COMSNETS 2014: 1-6 - [c57]Manimaran Sivasamy Sivamurugan, Balaraman Ravindran:
RRTPI: Policy iteration on continuous domains using rapidly-exploring random trees. ICRA 2014: 4362-4367 - [c56]A. P. Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas C. Raykar, Amrita Saha:
An Autoencoder Approach to Learning Bilingual Word Representations. NIPS 2014: 1853-1861 - [c55]Addwiteey Chrungoo, S. S. Manimaran, Balaraman Ravindran:
Activity Recognition for Natural Human Robot Interaction. ICSR 2014: 84-94 - [e3]Balaraman Ravindran, Kamalakar Karlapalem:
Proceedings of the 1st IKDD Conference on Data Sciences, Delhi, India, March 21 - 23, 2014. ACM 2014, ISBN 978-1-4503-2475-5 [contents] - [i4]Tomasz Pawel Michalak, Aadithya V. Karthik, Piotr L. Szczepanski, Balaraman Ravindran, Nicholas R. Jennings:
Efficient Computation of the Shapley Value for Game-Theoretic Network Centrality. CoRR abs/1402.0567 (2014) - [i3]A. P. Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas C. Raykar, Amrita Saha:
An Autoencoder Approach to Learning Bilingual Word Representations. CoRR abs/1402.1454 (2014) - [i2]Pratik Vinay Gupte, Balaraman Ravindran:
Scalable Positional Analysis for Studying Evolution of Nodes in Networks. CoRR abs/1402.3797 (2014) - 2013
- [j6]Tomasz P. Michalak, Aadithya V. Karthik, Piotr L. Szczepanski, Balaraman Ravindran, Nicholas R. Jennings:
Efficient Computation of the Shapley Value for Game-Theoretic Network Centrality. J. Artif. Intell. Res. 46: 607-650 (2013) - [c54]Deepak Pai, Balaraman Ravindran, Shyam Rajagopalan, Ramesh Srinivasaraghavan:
Automated faceted reporting for web analytics. Web-KRM@CIKM 2013: 9-16 - [c53]Balaji Vasan Srinivasan, Anandhavelu Natarajan, Ritwik Sinha, Vineet Gupta, Shriram Revankar, Balaraman Ravindran:
Will your facebook post be engaging? UEO@CIKM 2013: 25-28 - [c52]Lakshmi Ramachandran, Balaraman Ravindran, Edward F. Gehringer:
Determining Review Coverage by Extracting Topic Sentences Using A Graph-based Clustering Approach. EDM 2013: 346-347 - [c51]Debarun Kar, Anand Kumar, Sutanu Chakraborti, Balaraman Ravindran:
iCaseViz: Learning Case Similarities through Interaction with a Case Base Visualizer. ICCBR 2013: 203-217 - [c50]Nilanjan Banerjee, Dipanjan Chakraborty, Anupam Joshi, Sumit Mittal, Angshu Rai, Balaraman Ravindran:
Detection of Real-Time Intentions from Micro-blogs. MobiQuitous 2013: 116-128 - [c49]Swapna Raj Prabakara Raj, Balaraman Ravindran:
Incremental Constrained Clustering: A Decision Theoretic Approach. PAKDD Workshops 2013: 475-486 - 2012
- [c48]Arun Tejasvi Chaganty, Prateek Gaur, Balaraman Ravindran:
Learning in a small world. AAMAS 2012: 391-397 - [c47]Saradindu Kar, Deepak Vijayakeerthi, Ashish V. Tendulkar, Balaraman Ravindran:
Functional site prediction by exploiting correlations between labels of interacting residues. BCB 2012: 76-83 - [c46]R. Rangadurai Karthick, Vipul P. Hattiwale, Balaraman Ravindran:
Adaptive network intrusion detection system using a hybrid approach. COMSNETS 2012: 1-7 - [c45]Pradyot Korupolu V. N., Manimaran Sivasamy Sivamurugan, Balaraman Ravindran:
Instructing a Reinforcement Learner. FLAIRS 2012 - [c44]Pragathi Priyadharsini Balasubramani, Balaraman Ravindran, V. Srinivasa Chakravarthy:
Understanding the Role of Serotonin in Basal Ganglia through a Unified Model. ICANN (1) 2012: 467-473 - [c43]Debarun Kar, Sutanu Chakraborti, Balaraman Ravindran:
Feature Weighting and Confidence Based Prediction for Case Based Reasoning Systems. ICCBR 2012: 211-225 - [c42]José I. Nuñez-Varela, Balaraman Ravindran, Jeremy L. Wyatt:
Where do i look now? Gaze allocation during visually guided manipulation. ICRA 2012: 4444-4449 - [c41]Nilanjan Banerjee, Dipanjan Chakraborty, Anupam Joshi, Sumit Mittal, Angshu Rai, Balaraman Ravindran:
Towards Analyzing Micro-Blogs for Detection and Classification of Real-Time Intentions. ICWSM 2012 - [c40]José I. Nuñez-Varela, Balaraman Ravindran, Jeremy L. Wyatt:
Gaze Allocation Analysis for a Visually Guided Manipulation Task. SAB 2012: 44-53 - [c39]Pradyot Korupolu V. N., S. S. Manimaran, Balaraman Ravindran, Sriraam Natarajan:
Integrating Human Instructions and Reinforcement Learners: An SRL Approach. StarAI@UAI 2012 - [i1]Ananda Narayanan B., Balaraman Ravindran:
Fractional Moments on Bandit Problems. CoRR abs/1202.3750 (2012) - 2011
- [j5]S. Shivashankar, S. Srivathsan, Balaraman Ravindran, Ashish V. Tendulkar:
Multi-view methods for protein structure comparison using latent dirichlet allocation. Bioinform. 27(13): 61-68 (2011) - [j4]K. N. Magdoom, Deepak Subramanian, V. Srinivasa Chakravarthy, Balaraman Ravindran, Shun-ichi Amari, N. Meenakshisundaram:
Modeling Basal Ganglia for Understanding Parkinsonian Reaching Movements. Neural Comput. 23(2): 477-516 (2011) - [c38]Rajagopalan Vijayasarathy, Serugudi Venkataraman Raghavan, Balaraman Ravindran:
A system approach to network modeling for DDoS detection using a Naìve Bayesian classifier. COMSNETS 2011: 1-10 - [c37]Munu Sairamesh, Balaraman Ravindran:
Options with Exceptions. EWRL 2011: 165-176 - [c36]Ankit Malpani, Balaraman Ravindran, Hema A. Murthy:
Personalized Intelligent Tutoring System Using Reinforcement Learning. FLAIRS 2011 - [c35]Prabakararaj Swapna Raj, Balaraman Ravindran:
Utility Driven Clustering. FLAIRS 2011 - [c34]Ananda Narayanan B., Balaraman Ravindran:
Fractional Moments on Bandit Problems. UAI 2011: 531-538 - 2010
- [j3]M. Saravanan, Balaraman Ravindran:
Identification of Rhetorical Roles for Segmentation and Summarization of a Legal Judgment. Artif. Intell. Law 18(1): 45-76 (2010) - [c33]Aadithya V. Karthik, Balaraman Ravindran:
Game theoretic network centrality: exact formulas and efficient algorithms. AAMAS 2010: 1459-1460 - [c32]S. Shivashankar, Balaraman Ravindran:
Multi Grain Sentiment Analysis using Collective Classification. ECAI 2010: 823-828 - [c31]Prabakararaj Swapna Raj, Balaraman Ravindran:
Mining Actionable Patterns. FLAIRS 2010 - [c30]Yousuf Aboobaker Sait, Balaraman Ravindran:
Visual Object Detection using Frequent Pattern Mining. FLAIRS 2010 - [c29]Maya Manaithunai, V. Srinivasa Chakravarthy, Balaraman Ravindran:
An Oscillatory Neural Network Model for Birdsong Learning and Generation. ICANN (2) 2010: 210-215 - [c28]Aswin N. Raghavan, Harini Ananthapadmanaban, Manimaran Sivasamy Sivamurugan, Balaraman Ravindran:
Accurate mobile robot localization in indoor environments using bluetooth. ICRA 2010: 4391-4396 - [c27]Balaji Lakshmanan, Balaraman Ravindran:
Transfer learning across heterogeneous robots with action sequence mapping. IROS 2010: 3251-3256 - [c26]Aadithya V. Karthik, Balaraman Ravindran, Tomasz P. Michalak, Nicholas R. Jennings:
Efficient Computation of the Shapley Value for Centrality in Networks. WINE 2010: 1-13 - [e2]Mohammed Javeed Zaki, Jeffrey Xu Yu, Balaraman Ravindran, Vikram Pudi:
Advances in Knowledge Discovery and Data Mining, 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part I. Lecture Notes in Computer Science 6118, Springer 2010, ISBN 978-3-642-13656-6 [contents] - [e1]Mohammed Javeed Zaki, Jeffrey Xu Yu, Balaraman Ravindran, Vikram Pudi:
Advances in Knowledge Discovery and Data Mining, 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part II. Lecture Notes in Computer Science 6119, Springer 2010, ISBN 978-3-642-13671-9 [contents]
2000 – 2009
- 2009
- [j2]M. Saravanan, Balaraman Ravindran, S. Raman:
Improving legal information retrieval using an ontological framework. Artif. Intell. Law 17(2): 101-124 (2009) - [c25]Jyotika Bahuguna, Balaraman Ravindran, K. Madhava Krishna:
MDP based active localization for multiple robots. CASE 2009: 635-640 - [c24]Kiran Kate, Balaraman Ravindran:
Epsilon Equitable Partition: A positional analysis method for large social networks. COMAD 2009 - 2008
- [c23]Swapna Raj Prabakara Raj, Balaraman Ravindran:
Personalized Web-page Rendering System. COMAD 2008: 30-39 - [c22]Sriram Raghavan, Balaraman Ravindran:
Successive refinement algorithms for distributed area coverage using mobile robots. Bangalore Compute Conf. 2008: 20 - [c21]Aniket Ray, Vikas Kumar, Balaraman Ravindran, Lingam Gopal, Aditya Verma:
Machine Learning to Predict the Incidence of Retinopathy of Prematurity. FLAIRS 2008: 300-305 - [c20]P. Swaminathan, Balaraman Ravindran:
Co-SOFT-Clustering: An Information Theoretic Approach to Obtain Overlapping Clusters from Co-Occurrence Data. FLAIRS 2008: 320-321 - [c19]Rachit Arora, Balaraman Ravindran:
Latent Dirichlet Allocation and Singular Value Decomposition Based Multi-document Summarization. ICDM 2008: 713-718 - [c18]Shravan Matthur Narayanamurthy, Balaraman Ravindran:
On the hardness of finding symmetries in Markov decision processes. ICML 2008: 688-695 - [c17]Dinakar Jayarajan, Dipti Deodhare, Balaraman Ravindran:
Lexical Chains as Document Features. IJCNLP 2008: 111-117 - [c16]M. Saravanan, Balaraman Ravindran, S. Raman:
Automatic Identification of Rhetorical Roles using Conditional Random Fields for Legal Document Summarization. IJCNLP 2008: 481-488 - [c15]Rachit Arora, Balaraman Ravindran:
Latent dirichlet allocation based multi-document summarization. AND 2008: 91-97 - 2007
- [c14]Sriram Raghavan, Balaraman Ravindran:
Profiling Pseudonet Architecture for Coordinating Mobile Robots. COMSWARE 2007 - [c13]B. H. Sreenivasa Sarma, Balaraman Ravindran:
Intelligent Tutoring Systems using Reinforcement Learning to teach Autistic Students. HOIT 2007: 65-78 - [c12]Balaraman Ravindran, Andrew G. Barto, Vimal Mathew:
Deictic Option Schemas. IJCAI 2007: 1023-1028 - [c11]Pranjal Awasthi, Aakanksha Gagrani, Balaraman Ravindran:
Image Modeling Using Tree Structured Conditional Random Fields. IJCAI 2007: 2060-2065 - [c10]Shravan Matthur Narayanamurthy, Balaraman Ravindran:
Efficiently Exploiting Symmetries in Real Time Dynamic Programming. IJCAI 2007: 2556-2561 - [c9]M. Saravanan, Balaraman Ravindran, S. Raman:
Using Legal Ontology for Query Enhancement in Generating a Document Summary. JURIX 2007: 171-172 - [c8]Sriram Raghavan, Balaraman Ravindran:
Homogeneous Hierarchical Composition of Areas in Multi-robot Area Coverage. SARA 2007: 300-313 - 2006
- [j1]M. Saravanan, S. Raman, Balaraman Ravindran:
A Probabilistic Approach to Multi-Document Summarization for Generating a Tiled Summary. Int. J. Comput. Intell. Appl. 6(2): 231-243 (2006) - [c7]Aakanksha Gagrani, Lalit Gupta, Balaraman Ravindran, Sukhendu Das, Pinaki Roychowdhury, V. K. Panchal:
A Hierarchical Approach to Landform Classification of Satellite Images Using a Fusion Strategy. ICVGIP 2006: 140-151 - [c6]M. Saravanan, Balaraman Ravindran, S. Raman:
Improving Legal Document Summarization Using Graphical Models. JURIX 2006: 51-60 - 2005
- [c5]R. Manimegalai, E. Siva Soumya, Vaishnavi Muralidharan, Balaraman Ravindran, V. Kamakoti, Dinesh Bhatia:
Placement and Routing for 3D-FPGAs Using Reinforcement Learning and Support Vector Machines. VLSI Design 2005: 451-456 - 2003
- [c4]Balaraman Ravindran, Andrew G. Barto:
Relativized Options: Choosing the Right Transformation. ICML 2003: 608-615 - [c3]Balaraman Ravindran, Andrew G. Barto:
SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes. IJCAI 2003: 1011-1018 - 2002
- [c2]Balaraman Ravindran, Andrew G. Barto:
Model Minimization in Hierarchical Reinforcement Learning. SARA 2002: 196-211
1990 – 1999
- 1998
- [c1]Richard S. Sutton, Satinder Singh, Doina Precup, Balaraman Ravindran:
Improved Switching among Temporally Abstract Actions. NIPS 1998: 1066-1072
Coauthor Index
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