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ORCIDNaren Ramakrishnan
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- affiliation: Virginia Tech, Blacksburg, Virginia, USA
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2020 – today
- 2023
[j129]Vandana Sreedharan, Upinder S. Bhalla, Naren Ramakrishnan:
Using sensitivity analyses to understand bistable system behavior. BMC Bioinform. 24(1): 136 (2023)- [j128]Subhodip Biswas
, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Memetic Algorithms for Spatial Partitioning Problems. ACM Trans. Spatial Algorithms Syst. 9(1): 5:1-5:31 (2023) - [i74]Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan:
Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency. CoRR abs/2305.08246 (2023) - 2022
- [j127]K. S. M. Tozammel Hossain, Hrayr Harutyunyan, Yue Ning, Brendan Kennedy, Naren Ramakrishnan, Aram Galstyan:
Identifying geopolitical event precursors using attention-based LSTMs. Frontiers Artif. Intell. 5 (2022) - [j126]Liang Zhao, Yuyang Gao, Jieping Ye, Feng Chen, Yanfang Ye, Chang-Tien Lu, Naren Ramakrishnan:
Spatio-Temporal Event Forecasting Using Incremental Multi-Source Feature Learning. ACM Trans. Knowl. Discov. Data 16(2): 40:1-40:28 (2022) - [c181]Zonghan Zhang, Subhodip Biswas, Fanglan Chen, Kaiqun Fu, Taoran Ji, Chang-Tien Lu, Naren Ramakrishnan, Zhiqian Chen:
Blocking Influence at Collective Level with Hard Constraints (Student Abstract). AAAI 2022: 13115-13116 - [c180]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Improving Zero-Shot Event Extraction via Sentence Simplification. CASE@EMNLP 2022: 32-43 - [c179]Gopikrishna Rathinavel, Nikhil Muralidhar, Timothy J. O'Shea, Naren Ramakrishnan:
Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. ICDM 2022: 1161-1166 - [c178]Debanjan Datta, Feng Chen, Naren Ramakrishnan:
Framing Algorithmic Recourse for Anomaly Detection. KDD 2022: 283-293 - [c177]Gopikrishna Rathinavel, Nikhil Muralidhar, Naren Ramakrishnan, Timothy J. O'Shea:
Efficient Generative Wireless Anomaly Detection for Next Generation Networks. MILCOM 2022: 594-599 - [i73]Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari, B. Aditya Prakash:
EINNs: Epidemiologically-Informed Neural Networks. CoRR abs/2202.10446 (2022) - [i72]Nikhil Muralidhar, Abdullah Zubair, Nathanael R. Weidler, Ryan M. Gerdes, Naren Ramakrishnan:
Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores. CoRR abs/2203.02095 (2022) - [i71]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Improving Zero-Shot Event Extraction via Sentence Simplification. CoRR abs/2204.02531 (2022) - [i70]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Sampling-based techniques for designing school boundaries. CoRR abs/2206.03703 (2022) - [i69]Debanjan Datta, Feng Chen, Naren Ramakrishnan:
Framing Algorithmic Recourse for Anomaly Detection. CoRR abs/2206.14384 (2022) - [i68]Raquib Bin Yousuf, Subhodip Biswas, Kulendra Kumar Kaushal, James Dunham, Rebecca Gelles, Sathappan Muthiah, Nathan Self, Patrick Butler, Naren Ramakrishnan:
Lessons from Deep Learning applied to Scholarly Information Extraction: What Works, What Doesn't, and Future Directions. CoRR abs/2207.04029 (2022) - [i67]Mandar Sharma, Ajay Gogineni, Naren Ramakrishnan:
Innovations in Neural Data-to-text Generation. CoRR abs/2207.12571 (2022) - [i66]Debanjan Datta, Sathappan Muthiah, John Simeone, Amelia Meadows, Naren Ramakrishnan:
Scrutinizing Shipment Records To Thwart Illegal Timber Trade. CoRR abs/2208.00493 (2022) - [i65]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Memetic algorithms for Spatial Partitioning problems. CoRR abs/2208.02867 (2022) - [i64]Gopikrishna Rathinavel, Nikhil Muralidhar, Timothy J. O'Shea, Naren Ramakrishnan:
Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. CoRR abs/2210.02841 (2022) - [i63]Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan:
Overcoming Barriers to Skill Injection in Language Modeling: Case Study in Arithmetic. CoRR abs/2211.02098 (2022) - 2021
- [j125]Gubbi Vani HarshaRani, S. Moza, Naren Ramakrishnan, Upinder S. Bhalla:
SWITCHES: Searchable Web Interface for Topologies of CHEmical Switches. Bioinform. 37(16): 2504-2505 (2021) - [j124]Tian Shi, Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Neural Abstractive Text Summarization with Sequence-to-Sequence Models. Trans. Data Sci. 2(1): 1:1-1:37 (2021) - [j123]Arjun Choudhry, Mandar Sharma, Pramod Chundury, Thomas Kapler, Derek W. S. Gray, Naren Ramakrishnan, Niklas Elmqvist:
Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality. IEEE Trans. Vis. Comput. Graph. 27(2): 1332-1342 (2021) - [c176]Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash:
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. AAAI 2021: 4855-4863 - [c175]Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu:
Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications. AAAI 2021: 7953-7960 - [c174]Bing He, Caleb Ziems, Sandeep Soni, Naren Ramakrishnan, Diyi Yang, Srijan Kumar:
Racism is a virus: anti-asian hate and counterspeech in social media during the COVID-19 crisis. ASONAM 2021: 90-94 - [c173]Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu:
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information. ASONAM 2021: 168-175 - [c172]Nikhil Muralidhar, Abdullah Zubair, Nathanael R. Weidler, Ryan M. Gerdes, Naren Ramakrishnan:
Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores. HOST 2021: 181-191 - [c171]Nikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields. ICDM 2021: 1246-1251 - [c170]Mandar Sharma, John S. Brownstein, Naren Ramakrishnan:
T3: Domain-Agnostic Neural Time-series Narration. ICDM 2021: 1324-1329 - [e3]Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty:
Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part I. Lecture Notes in Computer Science 12712, Springer 2021, ISBN 978-3-030-75761-8 [contents] - [e2]Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty:
Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part II. Lecture Notes in Computer Science 12713, Springer 2021, ISBN 978-3-030-75764-9 [contents] - [e1]Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty:
Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part III. Lecture Notes in Computer Science 12714, Springer 2021, ISBN 978-3-030-75767-0 [contents] - [i62]Alexander Rodríguez, Bijaya Adhikari, Naren Ramakrishnan, B. Aditya Prakash:
Incorporating Expert Guidance in Epidemic Forecasting. CoRR abs/2101.10247 (2021) - [i61]Debanjan Datta, Sathappan Muthiah, Naren Ramakrishnan:
Detecting Anomalies Through Contrast in Heterogeneous Data. CoRR abs/2104.01156 (2021) - [i60]Nikhil Muralidhar, Sathappan Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays 'Skip' McCormick, Naren Ramakrishnan:
Using AntiPatterns to avoid MLOps Mistakes. CoRR abs/2107.00079 (2021) - [i59]Mandar Sharma, John S. Brownstein, Naren Ramakrishnan:
TCube: Domain-Agnostic Neural Time-series Narration. CoRR abs/2110.05633 (2021) - [i58]Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu:
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information. CoRR abs/2111.05199 (2021) - 2020
- [j122]Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems. Big Data 8(5): 431-449 (2020) - [j121]Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, Naren Ramakrishnan:
Online flu epidemiological deep modeling on disease contact network. GeoInformatica 24(2): 443-475 (2020) - [j120]Vanessa Cedeno-Mieles, Zhihao Hu, Yihui Ren, Xinwei Deng, Abhijin Adiga, Christopher L. Barrett, Noshir Contractor, Saliya Ekanayake, Joshua M. Epstein, Brian J. Goode, Gizem Korkmaz, Chris J. Kuhlman, Dustin Machi, Michael W. Macy, Madhav V. Marathe, Naren Ramakrishnan, S. S. Ravi, Parang Saraf, Nathan Self:
Networked experiments and modeling for producing collective identity in a group of human subjects using an iterative abduction framework. Soc. Netw. Anal. Min. 10(1): 11 (2020) - [j119]Nikhil Muralidhar, Anika Tabassum, Liangzhe Chen, Supriya Chinthavali, Naren Ramakrishnan, B. Aditya Prakash:
Cut-n-Reveal: Time Series Segmentations with Explanations. ACM Trans. Intell. Syst. Technol. 11(5): 53:1-53:26 (2020) - [j118]Yaser Keneshloo, Tian Shi, Naren Ramakrishnan, Chandan K. Reddy:
Deep Reinforcement Learning for Sequence-to-Sequence Models. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2469-2489 (2020) - [c169]Debanjan Datta, Mohammad Raihanul Islam, Nathan Self, Amelia Meadows, John Simeone, Willow Outhwaite, Chen Hin Keong, Amy Smith, Linda Walker, Naren Ramakrishnan:
Detecting Suspicious Timber Trades. AAAI 2020: 13248-13254 - [c168]Subhodip Biswas, Fanglan Chen, Andreea Sistrunk, Sathappan Muthiah, Zhiqian Chen, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan:
Geospatial Clustering for Balanced and Proximal Schools. AAAI 2020: 13358-13365 - [c167]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Incorporating domain knowledge into Memetic Algorithms for solving Spatial Optimization problems. SIGSPATIAL/GIS 2020: 25-35 - [c166]Fanglan Chen, Zhiqian Chen, Subhodip Biswas, Shuo Lei, Naren Ramakrishnan, Chang-Tien Lu:
Graph Convolutional Networks with Kalman Filtering for Traffic Prediction. SIGSPATIAL/GIS 2020: 135-138 - [c165]Rongrong Tao, Baojian Zhou, Feng Chen, David Mares, Patrick Butler, Naren Ramakrishnan, Ryan Kennedy:
Detecting Media Self-Censorship without Explicit Training Data. SDM 2020: 550-558 - [c164]Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly. SDM 2020: 559-567 - [i57]Arjun Choudhry, Mandar Sharma, Pramod Chundury, Thomas Kapler, Derek W. S. Gray, Naren Ramakrishnan, Niklas Elmqvist:
Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality. CoRR abs/2009.02649 (2020) - [i56]Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash:
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. CoRR abs/2009.11407 (2020) - [i55]Shengzhe Xu, Manish Marwah, Naren Ramakrishnan:
STAN: Synthetic Network Traffic Generation using Autoregressive Neural Models. CoRR abs/2009.12740 (2020) - [i54]Subhodip Biswas, Adam D. Cobb, Andreea Sistrunk, Naren Ramakrishnan, Brian Jalaian:
Better call Surrogates: A hybrid Evolutionary Algorithm for Hyperparameter optimization. CoRR abs/2012.06453 (2020)
2010 – 2019
- 2019
- [j117]Nannan Wu, Feng Chen, Jianxin Li, Jinpeng Huai, Baojian Zhou, Bo Li, Naren Ramakrishnan:
A Nonparametric Approach to Uncovering Connected Anomalies by Tree Shaped Priors. IEEE Trans. Knowl. Data Eng. 31(10): 1849-1862 (2019) - [j116]Maoyuan Sun, Jian Zhao, Hao Wu, Kurt Luther, Chris North, Naren Ramakrishnan:
The Effect of Edge Bundling and Seriation on Sensemaking of Biclusters in Bipartite Graphs. IEEE Trans. Vis. Comput. Graph. 25(10): 2983-2998 (2019) - [c163]Mohammad Raihanul Islam, Sathappan Muthiah, Naren Ramakrishnan:
RumorSleuth: joint detection of rumor veracity and user stance. ASONAM 2019: 131-136 - [c162]Taoran Ji, Xuchao Zhang, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan:
Feature driven learning framework for cybersecurity event detection. ASONAM 2019: 196-203 - [c161]Vanessa Cedeno-Mieles, Zhihao Hu, Xinwei Deng, Yihui Ren, Abhijin Adiga, Christopher L. Barrett, Saliya Ekanayake, Gizem Korkmaz, Chris J. Kuhlman, Dustin Machi, Madhav V. Marathe, S. S. Ravi, Brian J. Goode, Naren Ramakrishnan, Parang Saraf, Nathan Self, Noshir Contractor, Joshua M. Epstein, Michael W. Macy:
Mechanistic and data-driven agent-based models to explain human behavior in online networked group anagram games. ASONAM 2019: 357-364 - [c160]Nikhil Muralidhar, Sathappan Muthiah, Kiyoshi Nakayama, Ratnesh Sharma, Naren Ramakrishnan:
Multivariate Long-Term State Forecasting in Cyber-Physical Systems: A Sequence to Sequence Approach. IEEE BigData 2019: 543-552 - [c159]Mohammad Raihanul Islam, Sathappan Muthiah, Naren Ramakrishnan:
NActSeer: Predicting User Actions in Social Network using Graph Augmented Neural Network. CIKM 2019: 1793-1802 - [c158]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Andreea Sistrunk, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan:
REGAL: A Regionalization framework for school boundaries. SIGSPATIAL/GIS 2019: 544-547 - [c157]Taoran Ji, Zhiqian Chen, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan:
Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks. IJCAI 2019: 2621-2627 - [c156]Nikhil Muralidhar, Sathappan Muthiah, Naren Ramakrishnan:
DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems. IJCAI 2019: 3180-3186 - [c155]Bijaya Adhikari, Xinfeng Xu, Naren Ramakrishnan, B. Aditya Prakash:
EpiDeep: Exploiting Embeddings for Epidemic Forecasting. KDD 2019: 577-586 - [c154]Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan:
Mitigating Uncertainty in Document Classification. NAACL-HLT (1) 2019: 3126-3136 - [c153]Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Deep Transfer Reinforcement Learning for Text Summarization. SDM 2019: 675-683 - [c152]Maoyuan Sun, David Koop, Jian Zhao, Chris North, Naren Ramakrishnan:
Interactive Bicluster Aggregation in Bipartite Graphs. IEEE VIS (Short Papers) 2019: 246-250 - [c151]Zhihao Hu, Dustin Machi, Madhav V. Marathe, S. S. Ravi, Yihui Ren, Vanessa Cedeno-Mieles, Saliya Ekanayake, Xinwei Deng, Brian J. Goode, Naren Ramakrishnan, Parang Saraf, Nathan Self, Abhijin Adiga, Gizem Korkmaz, Chris J. Kuhlman:
On the Modeling and Agent-Based Simulation of a Cooperative Group Anagram Game. WSC 2019: 169-180 - [c150]Sneha Mehta, Mohammad Raihanul Islam, Huzefa Rangwala, Naren Ramakrishnan:
Event Detection using Hierarchical Multi-Aspect Attention. WWW 2019: 3079-3085 - [i53]Taoran Ji, Zhiqian Chen, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan:
Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks. CoRR abs/1905.10022 (2019) - [i52]Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan:
Mitigating Uncertainty in Document Classification. CoRR abs/1907.07590 (2019) - [i51]Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids. CoRR abs/1911.04240 (2019) - [i50]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Low Rank Factorization for Compact Multi-Head Self-Attention. CoRR abs/1912.00835 (2019) - 2018
- [j115]David R. Easterling, Layne T. Watson, Naren Ramakrishnan:
Probability-one homotopy methods for constrained clustering. J. Comput. Appl. Math. 343: 602-618 (2018) - [j114]Prithwish Chakraborty, Bryan L. Lewis, Stephen G. Eubank, John S. Brownstein, Madhav V. Marathe, Naren Ramakrishnan:
What to know before forecasting the flu. PLoS Comput. Biol. 14(10) (2018) - [j113]Hao Wu, Xinwei Deng, Naren Ramakrishnan:
Sparse estimation of multivariate Poisson log-normal models from count data. Stat. Anal. Data Min. 11(2): 66-77 (2018) - [j112]Nikhil Muralidhar, Chen Wang, Nathan Self, Marjan Momtazpour, Kiyoshi Nakayama, Ratnesh Sharma, Naren Ramakrishnan:
illiad: InteLLigent Invariant and Anomaly Detection in Cyber-Physical Systems. ACM Trans. Intell. Syst. Technol. 9(3): 35:1-35:20 (2018) - [j111]Hao Wu, Maoyuan Sun, Peng Mi, Nikolaj Tatti, Chris North, Naren Ramakrishnan:
Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models. ACM Trans. Knowl. Discov. Data 12(1): 7:1-7:34 (2018) - [j110]Hao Wu, Yue Ning, Prithwish Chakraborty, Jilles Vreeken, Nikolaj Tatti, Naren Ramakrishnan:
Generating Realistic Synthetic Population Datasets. ACM Trans. Knowl. Discov. Data 12(4): 45:1-45:22 (2018) - [j109]John E. Wenskovitch, Ian Crandell, Naren Ramakrishnan, Leanna House, Scotland Leman, Chris North:
Towards a Systematic Combination of Dimension Reduction and Clustering in Visual Analytics. IEEE Trans. Vis. Comput. Graph. 24(1): 131-141 (2018) - [c149]Pejman Khadivi, Ravi Tandon, Naren Ramakrishnan:
Flow of Information in Feed-Forward Denoising Neural Networks. ICCI*CC 2018: 166-173 - [c148]Yue Ning, Sathappan Muthiah, Naren Ramakrishnan, Huzefa Rangwala, David Mares:
When do Crowds Turn Violent? Uncovering Triggers from Media. ASONAM 2018: 77-82 - [c147]Yihui Ren, Vanessa Cedeno-Mieles, Zhihao Hu, Xinwei Deng, Abhijin Adiga, Christopher L. Barrett, Saliya Ekanayake, Brian J. Goode, Gizem Korkmaz, Chris J. Kuhlman, Dustin Machi, Madhav V. Marathe, Naren Ramakrishnan, S. S. Ravi, Parang Saraf, Nathan Self, Noshir Contractor, Joshua M. Epstein, Michael W. Macy:
Generative Modeling of Human Behavior and Social Interactions Using Abductive Analysis. ASONAM 2018: 413-420 - [c146]Taoran Ji, Kaiqun Fu, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan:
Multi-Task Learning for Transit Service Disruption Detection. ASONAM 2018: 634-641 - [c145]Nikhil Muralidhar, Mohammad Raihanul Islam, Manish Marwah, Anuj Karpatne, Naren Ramakrishnan:
Incorporating Prior Domain Knowledge into Deep Neural Networks. IEEE BigData 2018: 36-45 - [c144]Sujay Yadawadkar, Brian Mayer, Sanket Lokegaonkar, Mohammad Raihanul Islam, Naren Ramakrishnan, Miao Song, Michael Mollenhauer:
Identifying Distracted and Drowsy Drivers Using Naturalistic Driving Data. IEEE BigData 2018: 2019-2026 - [c143]Mohammad Raihanul Islam, Sathappan Muthiah, Bijaya Adhikari, B. Aditya Prakash, Naren Ramakrishnan:
DeepDiffuse: Predicting the 'Who' and 'When' in Cascades. ICDM 2018: 1055-1060 - [c142]Ting Hua, Chandan K. Reddy, Lei Zhang, Lijing Wang, Liang Zhao, Chang-Tien Lu, Naren Ramakrishnan:
Social Media based Simulation Models for Understanding Disease Dynamics. IJCAI 2018: 3797-3804 - [c141]Mohammad Raihanul Islam, B. Aditya Prakash, Naren Ramakrishnan:
SIGNet: Scalable Embeddings for Signed Networks. PAKDD (2) 2018: 157-169 - [c140]Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash:
Sub2Vec: Feature Learning for Subgraphs. PAKDD (2) 2018: 170-182 - [c139]Nasrin Akhter, Liang Zhao, Desmond Arias, Huzefa Rangwala, Naren Ramakrishnan:
Forecasting Gang Homicides with Multi-level Multi-task Learning. SBP-BRiMS 2018: 28-37 - [c138]Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan:
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. SDM 2018: 99-107 - [c137]Vanessa Cedeno-Mieles, Yihui Ren, Saliya Ekanayake, Brian J. Goode, Chris J. Kuhlman, Dustin Machi, Madhav V. Marathe, Henning S. Mortveit, Zhihao Hu, Xinwei Deng, Naren Ramakrishnan, Parang Saraf, Nathan Self, Noshir Contractor, Joshua M. Epstein, Michael W. Macy:
Pipelines and their Compositions for Modeling and Analysis of controlled Online Networked Social Science Experiments. WSC 2018: 774-785 - [i49]Yaser Keneshloo, Tian Shi, Naren Ramakrishnan, Chandan K. Reddy:
Deep Reinforcement Learning For Sequence to Sequence Models. CoRR abs/1805.09461 (2018) - [i48]Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Deep Transfer Reinforcement Learning for Text Summarization. CoRR abs/1810.06667 (2018) - [i47]Tian Shi, Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Neural Abstractive Text Summarization with Sequence-to-Sequence Models. CoRR abs/1812.02303 (2018) - 2017
- [j108]Liang Zhao, Junxiang Wang, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Spatial Event Forecasting in Social Media With Geographically Hierarchical Regularization. Proc. IEEE 105(10): 1953-1970 (2017) - [j107]Theodoros Rekatsinas, Saurav Ghosh, Sumiko R. Mekaru, Elaine O. Nsoesie, John S. Brownstein, Lise Getoor, Naren Ramakrishnan:
Forecasting rare disease outbreaks from open source indicators. Stat. Anal. Data Min. 10(2): 136-150 (2017) - [j106]Xiaokui Shu, Danfeng (Daphne) Yao, Naren Ramakrishnan, Trent Jaeger:
Long-Span Program Behavior Modeling and Attack Detection. ACM Trans. Priv. Secur. 20(4): 12:1-12:28 (2017) - [j105]Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting. IEEE Trans. Knowl. Data Eng. 29(5): 1059-1072 (2017) - [c136]Rupinder Paul Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik R. Smith, Christopher Adams, Naren Ramakrishnan:
Determining Relative Airport Threats from News and Social Media. AAAI 2017: 4701-4707 - [c135]Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu, Naren Ramakrishnan:
Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data. CIKM 2017: 507-516 - [c134]Rupinder Paul Khandpur, Taoran Ji, Steve T. K. Jan, Gang Wang, Chang-Tien Lu, Naren Ramakrishnan:
Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media. CIKM 2017: 1049-1057 - [c133]Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash:
Distributed Representations of Subgraphs. ICDM Workshops 2017: 111-117 - [c132]Fang Jin, Wei Wang, Prithwish Chakraborty, Nathan Self, Feng Chen, Naren Ramakrishnan:
Tracking Multiple Social Media for Stock Market Event Prediction. ICDM 2017: 16-30 - [c131]Saurav Ghosh, Prithwish Chakraborty, Bryan L. Lewis, Maimuna S. Majumder, Emily Cohn, John S. Brownstein, Madhav V. Marathe, Naren Ramakrishnan:
GELL: Automatic Extraction of Epidemiological Line Lists from Open Sources. KDD 2017: 1477-1485 - [c130]Yue Ning, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan:
A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. RecSys 2017: 23-31 - [c129]Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan, Wei Fan, Jieping Ye:
Pruning Decision Trees via Max-Heap Projection. SDM 2017: 10-18 - [c128]Fang Jin, Feng Chen, Rupinder Paul Khandpur, Chang-Tien Lu, Naren Ramakrishnan:
Absenteeism Detection in Social Media. SDM 2017: 606-614 - [r2]