Amit Sharma

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 83

Top Topics

Machine Learning

Causal Inference

Contextual Bandit

Top Venues

Publications

Aniket Vashishtha, Abhinav Kumar, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma
Teaching Transformers Causal Reasoning through Axiomatic Training. CoRR (2024)
Pragya Srivastava, Satvik Golechha, Amit Deshpande, Amit Sharma
NICE: To Optimize In-Context Examples or Not? ACL (1) (2024)
Pragya Srivastava, Satvik Golechha, Amit Deshpande, Amit Sharma
NICE: To Optimize In-Context Examples or Not? CoRR (2024)
Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)
Emre Kiciman, Robert Ness, Amit Sharma, Chenhao Tan
Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. CoRR (2023)
Parikshit Bansal, Amit Sharma
Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost. CoRR (2023)
Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan
Machine Explanations and Human Understanding. Trans. Mach. Learn. Res. 2023 (2023)
Abhinav Kumar, Amit Deshpande, Amit Sharma
Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations. NeurIPS (2023)
Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan
Machine Explanations and Human Understanding. FAccT (2023)
Parikshit Bansal, Amit Sharma
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers. ACL (1) (2023)
Jake M. Hofman, Angelos Chatzimparmpas, Amit Sharma, Duncan J. Watts, Jessica Hullman
Pre-registration for Predictive Modeling. CoRR (2023)
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma
Causal Inference Using LLM-Guided Discovery. CoRR (2023)
Jivat Neet Kaur, Emre Kiciman, Amit Sharma
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization. ICLR (2023)
Abhinav Kumar, Amit Deshpande, Amit Sharma
Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes. CoRR (2023)
Parikshit Bansal, Amit Sharma
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers. CoRR (2023)
Saloni Dash, Vineeth N. Balasubramanian, Amit Sharma
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals. WACV (2022)
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma
Matching Learned Causal Effects of Neural Networks with Domain Priors. ICML (2022)
Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian
Counterfactual Generation Under Confounding. CoRR (2022)
Parikshit Bansal, Yashoteja Prabhu, Emre Kiciman, Amit Sharma
Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems. CoRR (2022)
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. CoRR (2022)
Jivat Neet Kaur, Emre Kiciman, Amit Sharma
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization. CoRR (2022)
Abhinav Kumar, Chenhao Tan, Amit Sharma
Probing Classifiers are Unreliable for Concept Removal and Detection. NeurIPS (2022)
Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan
Machine Explanations and Human Understanding. CoRR (2022)
Abhinav Kumar, Chenhao Tan, Amit Sharma
Probing Classifiers are Unreliable for Concept Removal and Detection. CoRR (2022)
Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis
Omitted Variable Bias in Machine Learned Causal Models. CoRR (2021)
Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins
Sayer: Using Implicit Feedback to Optimize System Policies. CoRR (2021)
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. AIES (2021)
Sachin R. Pendse, Amit Sharma, Aditya Vashistha, Munmun De Choudhury, Neha Kumar
"Can I Not Be Suicidal on a Sunday?": Understanding Technology-Mediated Pathways to Mental Health Support. CHI (2021)
Naman Goel, Alfonso Amayuelas, Amit Deshpande, Amit Sharma
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective. AAAI (2021)
Prateek Chanda, Amogh Wagh, Jemimah A. Johnson, Swaraj Renghe, Vageesh Chandramouli, George Mathews, Sapna Behar, Poornima Bhola, Girish N. Rao, Paulomi Sudhir, T. K. Srikanth, Amit Sharma, Seema Mehrotra
MINDNOTES : A Mobile Platform to enable users to break stigma around mental health and connect with therapists. CSCW Companion (2021)
Divyat Mahajan, Shruti Tople, Amit Sharma
Domain Generalization using Causal Matching. ICML (2021)
Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Aleksandrs Slivkins, Amit Sharma
Sayer: Using Implicit Feedback to Optimize System Policies. SoCC (2021)
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. WSDM (2021)
Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atilim Günes Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr
Technology Readiness Levels for Machine Learning Systems. CoRR (2021)
Amit Sharma, Vasilis Syrgkanis, Cheng Zhang, Emre Kiciman
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions. CoRR (2021)
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Causally Constrained Data Synthesis for Private Data Release. CoRR (2021)
Divyat Mahajan, Shruti Tople, Amit Sharma
The Connection between Out-of-Distribution Generalization and Privacy of ML Models. CoRR (2021)
Ramaravind Kommiya Mothilal, Amit Sharma, Chenhao Tan
Explaining machine learning classifiers through diverse counterfactual explanations. FAT* (2020)
Devansh Mehta, Ramaravind Kommiya Mothilal, Alok Sharma, William Thies, Amit Sharma
Using Mobile Airtime Credits to Incentivize Learning, Sharing and Survey Response: Experiences from the Field. COMPASS (2020)
Divyat Mahajan, Shruti Tople, Amit Sharma
Domain Generalization using Causal Matching. CoRR (2020)
Amit Sharma, Emre Kiciman
Causal Inference and Counterfactual Reasoning. COMAD/CODS (2020)
Taisa Kushner, Amit Sharma
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums. WWW (2020)
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. CoRR (2020)
Taisa Kushner, Amit Sharma
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums. CoRR (2020)
Amit Sharma, Emre Kiciman
DoWhy: An End-to-End Library for Causal Inference. CoRR (2020)
Shruti Tople, Amit Sharma, Aditya Nori
Alleviating Privacy Attacks via Causal Learning. ICML (2020)
Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava, Alok Sharma, Anurag Shukla, Vishnu Prasad, Venkanna U, Amit Sharma, Kalika Bali
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi. CoRR (2020)
Naman Goel, Alfonso Amayuelas, Amit Deshpande, Amit Sharma
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective. CoRR (2020)
Saloni Dash, Amit Sharma
Counterfactual Generation and Fairness Evaluation Using Adversarially Learned Inference. CoRR (2020)
Koustuv Saha, Amit Sharma
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities. ICWSM (2020)
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. CoRR (2020)
Devansh Mehta, Alok Sharma, Ramaravind Kommiya Mothilal, Chiraag, Anurag Shukla, Vishnu Prasad, William Thies, Venkanna U, Colin Scott, Amit Sharma
Facilitating Media Distribution with Monetary Incentives. CHI Extended Abstracts (2020)
Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma
Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms. ICWSM (2020)
Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava, Alok Sharma, Anurag Shukla, Vishnu Prasad, Venkanna U, Amit Sharma, Kalika Bali
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi. LREC (2020)
Sachin R. Pendse, Faisal M. Lalani, Munmun De Choudhury, Amit Sharma, Neha Kumar
"Like Shock Absorbers": Understanding the Human Infrastructures of Technology-Mediated Mental Health Support. CHI (2020)
Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma
Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms. CoRR (2020)
Saiganesh Swaminathan, Indrani Medhi-Thies, Devansh Mehta, Edward Cutrell, Amit Sharma, William Thies
Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns. Proc. ACM Hum. Comput. Interact. 3 (CSCW) (2019)
Divyat Mahajan, Chenhao Tan, Amit Sharma
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers. CoRR (2019)
Ramaravind Kommiya Mothilal, Amulya Yadav, Amit Sharma
Optimizing peer referrals for public awareness using contextual bandits. COMPASS (2019)
Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data. CoRR (2019)
Sachin R. Pendse, Naveena Karusala, Divya Siddarth, Pattie Gonsalves, Seema Mehrotra, John A. Naslund, Mamta Sood, Neha Kumar, Amit Sharma
Mental health in the global south: challenges and opportunities in HCI for development. COMPASS (2019)
Ramaravind Kommiya Mothilal, Devansh Mehta, Alok Sharma, William Thies, Amit Sharma
Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness. CSCW Companion (2019)
Yada Pruksachatkun, Sachin R. Pendse, Amit Sharma
Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums. CHI (2019)
Ramaravind Kommiya Mothilal, Amit Sharma, Chenhao Tan
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations. CoRR (2019)
Karn Dubey, Palash Gupta, Rachna Shriwas, Gayatri Gulvady, Amit Sharma
Learnings from deploying a voice-based social platform for people with disability. COMPASS (2019)
Arpita Biswas, Siddharth Barman, Amit Deshpande, Amit Sharma
Quantifying Infra-Marginality and Its Trade-off with Group Fairness. CoRR (2019)
Emre Kiciman, Amit Sharma
Causal Inference and Counterfactual Reasoning (3hr Tutorial). WSDM (2019)
Shruti Tople, Amit Sharma, Aditya Nori
Alleviating Privacy Attacks via Causal Learning. CoRR (2019)
Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data. KDD (2019)
Jisun An, Rumi Chunara, David J. Crandall, Darian Frajberg, Megan French, Bernard J. Jansen, Juhi Kulshrestha, Yelena Mejova, Daniel M. Romero, Joni Salminen, Amit Sharma, Amit P. Sheth, Chenhao Tan, Samuel Hardman Taylor, Sanjaya Wijeratne
Reports of the Workshops Held at the 2018 International AAAI Conference on Web and Social Media. AI Mag. 39 (4) (2018)
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz
Auditing Search Engines for Differential Satisfaction Across Demographics. WWW (Companion Volume) (2017)
Michael D. Ekstrand, Amit Sharma
FATREC Workshop on Responsible Recommendation. RecSys (2017)
Mathias Lécuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins
Harvesting Randomness to Optimize Distributed Systems. HotNets (2017)
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz
Auditing Search Engines for Differential Satisfaction Across Demographics. CoRR (2017)
Amit Sharma, Dan Cosley
Distinguishing between Personal Preferences and Social Influence in Online Activity Feeds. CoRR (2016)
Travis Martin, Jake M. Hofman, Amit Sharma, Ashton Anderson, Duncan J. Watts
Exploring Limits to Prediction in Complex Social Systems. WWW (2016)
Samuel Barbosa, Dan Cosley, Amit Sharma, Roberto M. Cesar Jr.
Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand Behavior. WWW (2016)
Benjamin Shulman, Amit Sharma, Dan Cosley
Predictability of Popularity: Gaps between Prediction and Understanding. CoRR (2016)
Samuel Barbosa, Dan Cosley, Amit Sharma, Roberto M. Cesar Jr.
Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand Behavior. CoRR (2016)
Amit Sharma, Jake M. Hofman, Duncan J. Watts
Split-door criterion for causal identification: Automatic search for natural experiments. CoRR (2016)
Travis Martin, Jake M. Hofman, Amit Sharma, Ashton Anderson, Duncan J. Watts
Exploring limits to prediction in complex social systems. CoRR (2016)
Benjamin Shulman, Amit Sharma, Dan Cosley
Predictability of Popularity: Gaps between Prediction and Understanding. ICWSM (2016)
Amit Sharma, Dan Cosley
Distinguishing between Personal Preferences and Social Influence in Online Activity Feeds. CSCW (2016)
Amit Sharma, Dan Cosley
Studying and Modeling the Connection between People's Preferences and Content Sharing. CSCW (2015)
Amit Sharma, Jake M. Hofman, Duncan J. Watts
Estimating the Causal Impact of Recommendation Systems from Observational Data. CoRR (2015)
Amit Sharma, Jake M. Hofman, Duncan J. Watts
Estimating the Causal Impact of Recommendation Systems from Observational Data. EC (2015)
Amit Sharma, Dan Cosley
Studying and Modeling the Connection between People's Preferences and Content Sharing. CoRR (2014)
Amit Sharma
Modeling the effect of people's preferences and social forces on adopting and sharing items. RecSys (2014)
Amit Sharma, Baoshi Yan
Pairwise learning in recommendation: experiments with community recommendation on linkedin. RecSys (2013)
Amit Sharma, Dan Cosley
Do social explanations work?: studying and modeling the effects of social explanations in recommender systems. WWW (2013)
Priyankar Ghosh, Amit Sharma, Partha Pratim Chakrabarti, Pallab Dasgupta
Algorithms for Generating Ordered Solutions for Explicit AND/OR Structures : Extended Abstract. IJCAI (2013)
Amit Sharma, Mevlana Gemici, Dan Cosley
Friends, Strangers, and the Value of Ego Networks for Recommendation. ICWSM (2013)
Amit Sharma
PopCore: a system for network-centric recommendation. CSCW Companion (2013)
Amit Sharma, Dan Cosley
Do Social Explanations Work? Studying and Modeling the Effects of Social Explanations in Recommender Systems CoRR (2013)
Amit Sharma
A Research Platform for Recommendation within Social Networks. RSWeb@RecSys (2013)
Amit Sharma, Mevlana Gemici, Dan Cosley
Friends, Strangers, and the Value of Ego Networks for Recommendation CoRR (2013)
Vimmi Jaiswal, Amit Sharma, Akshat Verma
ReComp: QoS-aware recursive service composition at minimum cost. Integrated Network Management (2011)
Amit Sharma, Dan Cosley
Network-Centric Recommendation: Personalization with and in Social Networks. SocialCom/PASSAT (2011)