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ORCIDKush R. Varshney
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- affiliation: IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA
- affiliation (former): Massachusetts Institute of Technology, Cambridge, MA, USA
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2020 – today
- 2020
[j37]Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang:
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. J. Mach. Learn. Res. 21: 130:1-130:6 (2020)- [c73]Michiel A. Bakker, Humberto Riverón Valdés, Duy Patrick Tu, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland:
Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds. SafeAI@AAAI 2020: 41-53 - [c72]Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian:
Event-Driven Continuous Time Bayesian Networks. AAAI 2020: 3259-3266 - [c71]Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman:
A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications. AAAI 2020: 13369-13381 - [c70]Shubham Sharma, Yunfeng Zhang, Jesús M. Ríos Aliaga, Djallel Bouneffouf, Vinod Muthusamy, Kush R. Varshney:
Data Augmentation for Discrimination Prevention and Bias Disambiguation. AIES 2020: 358-364 - [c69]Yunfeng Zhang, Rachel K. E. Bellamy, Kush R. Varshney:
Joint Optimization of AI Fairness and Utility: A Human-Centered Approach. AIES 2020: 400-406 - [c68]Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel Brat, David A. Sontag, Kush R. Varshney:
Characterization of Overlap in Observational Studies. AISTATS 2020: 788-798 - [c67]Michael Hind, Stephanie Houde, Jacquelyn Martino, Aleksandra Mojsilovic, David Piorkowski, John T. Richards, Kush R. Varshney:
Experiences with Improving the Transparency of AI Models and Services. CHI Extended Abstracts 2020: 1-8 - [c66]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines. CHIL 2020: 19-29 - [c65]Kush R. Varshney:
On Mismatched Detection and Safe, Trustworthy Machine Learning. CISS 2020: 1-4 - [c64]Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang:
AI explainability 360: hands-on tutorial. FAT* 2020: 696 - [c63]Samuel C. Maina, Reginald E. Bryant, William O. Ogallo, Kush R. Varshney, Skyler Speakman, Celia Cintas, Aisha Walcott-Bryant, Robert-Florian Samoilescu, Komminist Weldemariam:
Preservation of Anomalous Subgroups On Variational Autoencoder Transformed Data. ICASSP 2020: 3627-3631 - [c62]Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar:
Invariant Risk Minimization Games. ICML 2020: 145-155 - [c61]Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney:
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing. ICML 2020: 2803-2813 - [c60]William Ogallo, Skyler Speakman, Victor Akinwande, Kush R. Varshney, Aisha Walcott-Bryant, Charity Wayua, Komminist Weldemariam:
Inspection of Blackbox Models for Evaluating Vulnerability in Maternal, Newborn, and Child Health. IJCAI 2020: 5282-5284 - [c59]Prithwish Chakraborty, Bum Chul Kwon, Sanjoy Dey, Amit Dhurandhar, Daniel Gruen, Kenney Ng, Daby Sow, Kush R. Varshney:
Tutorial on Human-Centered Explainability for Healthcare. KDD 2020: 3547-3548 - [c58]Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella
, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney:
Fairness of Classifiers Across Skin Tones in Dermatology. MICCAI (6) 2020: 320-329 - [i60]Yunfeng Zhang, Rachel K. E. Bellamy, Kush R. Varshney:
Joint Optimization of AI Fairness and Utility: A Human-Centered Approach. CoRR abs/2002.01621 (2020) - [i59]Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar:
Invariant Risk Minimization Games. CoRR abs/2002.04692 (2020) - [i58]Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney:
Fair Data Integration. CoRR abs/2006.06053 (2020) - [i57]Stacy Hobson, Michael Hind, Aleksandra Mojsilovic, Kush R. Varshney:
Trust and Transparency in Contact Tracing Applications. CoRR abs/2006.11356 (2020) - [i56]Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett:
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making. CoRR abs/2010.07938 (2020) - [i55]Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney:
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective. CoRR abs/2010.16412 (2020) - [i54]Kartik Ahuja, Amit Dhurandhar, Kush R. Varshney:
Learning to Initialize Gradient Descent Using Gradient Descent. CoRR abs/2012.12141 (2020)
2010 – 2019
- 2019
- [j36]Kush R. Varshney:
Trustworthy machine learning and artificial intelligence. XRDS 25(3): 26-29 (2019) - [j35]Lav R. Varshney, Florian Pinel, Kush R. Varshney, Debarun Bhattacharjya, Angela Schörgendorfer, Yi-Min Chee:
A big data approach to computational creativity: The curious case of Chef Watson. IBM J. Res. Dev. 63(1): 7:1-7:18 (2019) - [j34]Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, F. Rossi:
Teaching AI agents ethical values using reinforcement learning and policy orchestration. IBM J. Res. Dev. 63(4/5): 2:1-2:9 (2019) - [j33]Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney:
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network. IBM J. Res. Dev. 63(4/5): 3:1-3:9 (2019) - [j32]Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang:
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM J. Res. Dev. 63(4/5): 4:1-4:15 (2019) - [j31]Matthew Arnold, Rachel K. E. Bellamy, Michael Hind, Stephanie Houde, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Alexandra Olteanu, David Piorkowski, Darrell Reimer, John T. Richards, Jason Tsay, Kush R. Varshney:
FactSheets: Increasing trust in AI services through supplier's declarations of conformity. IBM J. Res. Dev. 63(4/5): 6:1-6:13 (2019) - [j30]Yaoli Mao, Dakuo Wang, Michael J. Muller, Kush R. Varshney, Ioana Baldini, Casey Dugan, Aleksandra Mojsilovic:
How Data ScientistsWork Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question? Proc. ACM Hum. Comput. Interact. 3(GROUP): 237:1-237:23 (2019) - [j29]Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang:
Think Your Artificial Intelligence Software Is Fair? Think Again. IEEE Softw. 36(4): 76-80 (2019) - [c57]Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty:
Fair Transfer Learning with Missing Protected Attributes. AIES 2019: 91-98 - [c56]Michael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
TED: Teaching AI to Explain its Decisions. AIES 2019: 123-129 - [c55]Pranay Kr. Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R. Varshney, Ruchir Puri:
Bias Mitigation Post-processing for Individual and Group Fairness. ICASSP 2019: 2847-2851 - [c54]Ravi Kiran Raman, Kush R. Varshney, Roman Vaculín, Nelson Kibichii Bore, Sekou L. Remy, Eleftheria Kyriaki Pissadaki, Michael Hind:
Constructing and Compressing Frames in Blockchain-based Verifiable Multi-party Computation. ICASSP 2019: 7500-7504 - [c53]Ravi Kiran Raman, Roman Vaculín, Michael Hind, Sekou L. Remy, Eleftheria Kyriaki Pissadaki, Nelson Kibichii Bore, Roozbeh Daneshvar, Biplav Srivastava, Kush R. Varshney:
A Scalable Blockchain Approach for Trusted Computation and Verifiable Simulation in Multi-Party Collaborations. IEEE ICBC 2019: 277-284 - [c52]Nelson Kibichii Bore, Ravi Kiran Raman, Isaac M. Markus, Sekou L. Remy, Oliver Bent, Michael Hind, Eleftheria Kyriaki Pissadaki, Biplav Srivastava, Roman Vaculín, Kush R. Varshney, Komminist Weldemariam:
Promoting Distributed Trust in Machine Learning and Computational Simulation. IEEE ICBC 2019: 311-319 - [c51]Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody:
Topological Data Analysis of Decision Boundaries with Application to Model Selection. ICML 2019: 5351-5360 - [c50]Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi:
Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration. IJCAI 2019: 6377-6381 - [i53]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines. CoRR abs/1905.03297 (2019) - [i52]Kush R. Varshney, Aleksandra Mojsilovic:
Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact. CoRR abs/1905.11519 (2019) - [i51]Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic:
Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning. CoRR abs/1906.02299 (2019) - [i50]Fredrik D. Johansson, Dennis Wei, Michael Oberst, Tian Gao, Gabriel Brat, David A. Sontag, Kush R. Varshney:
Characterization of Overlap in Observational Studies. CoRR abs/1907.04138 (2019) - [i49]Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang:
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques. CoRR abs/1909.03012 (2019) - [i48]Yaoli Mao, Dakuo Wang, Michael J. Muller, Kush R. Varshney, Ioana Baldini, Casey Dugan, Aleksandra Mojsilovic:
How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question? CoRR abs/1909.03486 (2019) - [i47]Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney:
An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy. CoRR abs/1910.07870 (2019) - [i46]Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney:
Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets. CoRR abs/1910.13268 (2019) - [i45]Michiel A. Bakker, Duy Patrick Tu, Humberto Riverón Valdés, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland:
DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning. CoRR abs/1910.13983 (2019) - [i44]Samuel C. Maina, Reginald E. Bryant, William O. Goal, Robert-Florian Samoilescu, Kush R. Varshney, Komminist Weldemariam:
Preservation of Anomalous Subgroups On Machine Learning Transformed Data. CoRR abs/1911.03674 (2019) - [i43]Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman:
Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies. CoRR abs/1911.07819 (2019) - [i42]Michael Hind, Stephanie Houde, Jacquelyn Martino, Aleksandra Mojsilovic, David Piorkowski, John T. Richards, Kush R. Varshney:
Experiences with Improving the Transparency of AI Models and Services. CoRR abs/1911.08293 (2019) - 2018
- [j28]Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis. IEEE J. Sel. Top. Signal Process. 12(5): 1106-1119 (2018) - [j27]Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Distribution-preserving k-anonymity. Stat. Anal. Data Min. 11(6): 253-270 (2018) - [c49]Jonathan Galsurkar, Moninder Singh, Lingfei Wu, Aditya Vempaty, Mikhail Sushkov, Devika Iyer, Serge Kapto, Kush R. Varshney:
Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search. AAAI 2018: 7753-7758 - [c48]Bhanukiran Vinzamuri, Kush R. Varshney:
False Discovery Rate Control with Concave Penalties Using Stability Selection. DSW 2018: 76-80 - [c47]Alexandra Olteanu, Carlos Castillo, Jeremy Boy, Kush R. Varshney:
The Effect of Extremist Violence on Hateful Speech Online. ICWSM 2018: 221-230 - [c46]Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney:
Semantic Representation of Data Science Programs. IJCAI 2018: 5847-5849 - [r2]Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic:
Legislative Prediction with Political and Social Network Analysis. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i41]Kush R. Varshney:
How an Electrical Engineer Became an Artificial Intelligence Researcher, a Multiphase Active Contours Analysis. CoRR abs/1803.11261 (2018) - [i40]Alexandra Olteanu, Carlos Castillo, Jeremy Boy, Kush R. Varshney:
The Effect of Extremist Violence on Hateful Speech Online. CoRR abs/1804.05704 (2018) - [i39]Bernat Guillen Pegueroles, Bhanukiran Vinzamuri, Karthikeyan Shanmugam, Steve Hedden, Jonathan D. Moyer, Kush R. Varshney:
Structure Learning from Time Series with False Discovery Control. CoRR abs/1805.09909 (2018) - [i38]Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney:
Fairness GAN. CoRR abs/1805.09910 (2018) - [i37]Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody:
Topological Data Analysis of Decision Boundaries with Application to Model Selection. CoRR abs/1805.09949 (2018) - [i36]Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic:
Teaching Meaningful Explanations. CoRR abs/1805.11648 (2018) - [i35]Kush R. Varshney, Prashant Khanduri, Pranay Sharma, Shan Zhang, Pramod K. Varshney:
Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory. CoRR abs/1806.09710 (2018) - [i34]Been Kim, Kush R. Varshney, Adrian Weller:
Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018). CoRR abs/1807.01308 (2018) - [i33]Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney:
Teaching machines to understand data science code by semantic enrichment of dataflow graphs. CoRR abs/1807.05691 (2018) - [i32]Michael Hind, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Alexandra Olteanu, Kush R. Varshney:
Increasing Trust in AI Services through Supplier's Declarations of Conformity. CoRR abs/1808.07261 (2018) - [i31]Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi:
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration. CoRR abs/1809.08343 (2018) - [i30]Ravi Kiran Raman, Roman Vaculín, Michael Hind, Sekou L. Remy, Eleftheria Kyriaki Pissadaki, Nelson Kibichii Bore, Roozbeh Daneshvar, Biplav Srivastava, Kush R. Varshney:
Trusted Multi-Party Computation and Verifiable Simulations: A Scalable Blockchain Approach. CoRR abs/1809.08438 (2018) - [i29]Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang:
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias. CoRR abs/1810.01943 (2018) - [i28]Nelson Kibichii Bore, Ravi Kiran Raman, Isaac M. Markus, Sekou L. Remy, Oliver Bent, Michael Hind, Eleftheria Kyriaki Pissadaki, Biplav Srivastava, Roman Vaculín, Kush R. Varshney, Komminist Weldemariam:
Promoting Distributed Trust in Machine Learning and Computational Simulation via a Blockchain Network. CoRR abs/1810.11126 (2018) - [i27]Minh N. B. Nguyen, Samuel Thomas, Anne E. Gattiker, Sujatha Kashyap, Kush R. Varshney:
SimplerVoice: A Key Message & Visual Description Generator System for Illiteracy. CoRR abs/1811.01299 (2018) - [i26]Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic:
TED: Teaching AI to Explain its Decisions. CoRR abs/1811.04896 (2018) - [i25]Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney:
Understanding Unequal Gender Classification Accuracy from Face Images. CoRR abs/1812.00099 (2018) - [i24]Pranay Kr. Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R. Varshney, Ruchir Puri:
Bias Mitigation Post-processing for Individual and Group Fairness. CoRR abs/1812.06135 (2018) - 2017
- [j26]Kush R. Varshney, Homa Alemzadeh:
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products. Big Data 5(3): 246-255 (2017) - [j25]Aleksandra Mojsilovic, Kush R. Varshney:
Preface: Data Science for Social Good. IBM J. Res. Dev. 61(6): 1-4 (2017) - [j24]Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Jan Houdek, M. Abubakar, Abdulwahab Alharbi, T. Braimoh, N. Ihebuzor, Aleksandra Mojsilovic, Kush R. Varshney:
Effectiveness of peer detailing in a diarrhea program in Nigeria. IBM J. Res. Dev. 61(6): 1 (2017) - [j23]H. Lamba, M. E. Helander, Moninder Singh, N. Lethif, Achyutram Bhamidipaty, S. A. Baset, Aleksandra Mojsilovic, Kush R. Varshney:
Understanding the ecospace of philanthropic projects. IBM J. Res. Dev. 61(6): 6 (2017) - [j22]Kien Pham, Prasanna Sattigeri, Amit Dhurandhar, A. C. Jacob, M. Vukovic, P. Chataigner, Juliana Freire, Aleksandra Mojsilovic, Kush R. Varshney:
Real-time understanding of humanitarian crises via targeted information retrieval. IBM J. Res. Dev. 61(6): 7 (2017) - [j21]Evan Patterson, Robert N. McBurney, H. Schmidt, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney:
Dataflow representation of data analyses: Toward a platform for collaborative data science. IBM J. Res. Dev. 61(6): 9 (2017) - [j20]Caitlin Kuhlman, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Aurelie C. Lozano, Lei Cao, C. Reddy, Aleksandra Mojsilovic, Kush R. Varshney:
How to foster innovation: A data-driven approach to measuring economic competitiveness. IBM J. Res. Dev. 61(6): 11 (2017) - [j19]Lav R. Varshney, Kush R. Varshney:
Decision Making With Quantized Priors Leads to Discrimination. Proc. IEEE 105(2): 241-255 (2017) - [j18]Kush R. Varshney:
Signal Processing for Social Good [In the Spotlight]. IEEE Signal Process. Mag. 34(3): 112-108 (2017) - [c45]Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney:
Machine Representation of Data Analyses: Towards a Platform for Collaborative Data Science. AAAI Spring Symposia 2017 - [c44]Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Kush R. Varshney, Aleksandra Mojsilovic:
Statistical Analysis of Peer Detailing for Children's Diarrhea Treatments. AAAI Spring Symposia 2017 - [c43]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Scalable Demand-Aware Recommendation. NIPS 2017: 2412-2421 - [c42]Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Optimized Pre-Processing for Discrimination Prevention. NIPS 2017: 3992-4001 - [c41]Alexandra Olteanu, Kartik Talamadupula, Kush R. Varshney:
The Limits of Abstract Evaluation Metrics: The Case of Hate Speech Detection. WebSci 2017: 405-406 - [i23]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Positive-Unlabeled Demand-Aware Recommendation. CoRR abs/1702.06347 (2017) - [i22]Flávio du Pin Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Optimized Data Pre-Processing for Discrimination Prevention. CoRR abs/1704.03354 (2017) - [i21]Been Kim, Dmitry M. Malioutov, Kush R. Varshney, Adrian Weller:
Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017). CoRR abs/1708.02666 (2017) - [i20]Samiulla Shaikh, Harit Vishwakarma, Sameep Mehta, Kush R. Varshney, Karthikeyan Natesan Ramamurthy, Dennis Wei:
An End-To-End Machine Learning Pipeline That Ensures Fairness Policies. CoRR abs/1710.06876 (2017) - [i19]Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Distribution-Preserving k-Anonymity. CoRR abs/1711.01514 (2017) - [i18]Tejas Dharamsi, Payel Das, Tejaswini Pedapati, Gregory Bramble, Vinod Muthusamy, Horst Samulowitz, Kush R. Varshney, Yuvaraj Rajamanickam, John Thomas, Justin Dauwels:
Neurology-as-a-Service for the Developing World. CoRR abs/1711.06195 (2017) - 2016
- [j17]Kush R. Varshney, Lav R. Varshney:
Olfactory signal processing. Digit. Signal Process. 48: 84-92 (2016) - [c40]Kush R. Varshney:
Interpretable machine learning via convex cardinal shape composition. Allerton 2016: 327-330 - [c39]Raya Horesh, Kush R. Varshney, Jinfeng Yi:
Information retrieval, fusion, completion, and clustering for employee expertise estimation. BigData 2016: 1385-1393 - [c38]Lav R. Varshney, Kush R. Varshney:
Fidelity loss in distribution-preserving anonymization and histogram equalization. CISS 2016: 24-29 - [c37]Aurelie C. Lozano, Prasanna Sattigeri, Aleksandra Mojsilovic, Kush R. Varshney:
Stable estimation of Granger-causal factors of country-level innovation. GlobalSIP 2016: 1290-1294 - [c36]Kush R. Varshney:
Engineering safety in machine learning. ITA 2016: 1-5 - [c35]Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang:
Dynamic matrix factorization with social influence. MLSP 2016: 1-6 - [c34]Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov:
Learning sparse two-level boolean rules. MLSP 2016: 1-6 - [i17]Kush R. Varshney:
Engineering Safety in Machine Learning. CoRR abs/1601.04126 (2016) - [i16]Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang:
Dynamic matrix factorization with social influence. CoRR abs/1604.06194 (2016) - [i15]Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov:
Interpretable Two-level Boolean Rule Learning for Classification. CoRR abs/1606.05798 (2016) - [i14]Prasanna Sattigeri, Aurélie C. Lozano, Aleksandra Mojsilovic, Kush R. Varshney, Mahmoud Naghshineh:
Understanding Innovation to Drive Sustainable Development. CoRR abs/1606.06177 (2016) - [i13]Kush R. Varshney:
Proceedings of the 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications. CoRR abs/1607.02450 (2016) - [i12]Been Kim, Dmitry M. Malioutov, Kush R. Varshney:
Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016). CoRR abs/1607.02531 (2016) - [i11]Kush R. Varshney, Homa Alemzadeh:
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products. CoRR abs/1610.01256 (2016) - 2015
- [j16]Kush R. Varshney, George H. Chen, Brian Abelson, Kendall Nowocin, Vivek Sakhrani, Ling Xu, Brian L. Spatocco:
Targeting Villages for Rural Development Using Satellite Image Analysis. Big Data 3(1): 41-53 (2015) - [j15]Kush R. Varshney, Dennis Wei, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic:
Data Challenges in Disease Response: The 2014 Ebola Outbreak and Beyond. ACM J. Data Inf. Qual. 6(2-3): 5:1-5:3 (2015) - [c33]Dennis Wei, Kush R. Varshney, Marcy Wagman:
Optigrow: People Analytics for Job Transfers. BigData Congress 2015: 535-542 - [c32]Sanjeeb Dash, Dmitry M. Malioutov, Kush R. Varshney:
Learning interpretable classification rules using sequential rowsampling. ICASSP 2015: 3337-3341 - [c31]Dennis Wei, Kush R. Varshney:
Robust binary hypothesis testing under contaminated likelihoods. ICASSP 2015: 3407-3411 - [c30]Kush R. Varshney, Karthikeyan Natesan Ramamurthy:
Persistent topology of decision boundaries. ICASSP 2015: 3931-3935 - [c29]Aleksandra Mojsilovic, Kush R. Varshney:
Assessing Expertise in the Enterprise: The Recommender Point of View. RecSys 2015: 231 - [c28]Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity.