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ORCIDAmit Sharma 0007
Person information
- affiliation: Microsoft Research, Bangalore, India
- affiliation (PhD 2015): Cornell University, Ithaca, NY, USA
- affiliation (former): IIT Kharagpur, India
Other persons with the same name
- Amit Sharma (aka: Amit Kumar Sharma) — disambiguation page
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Books and Theses
- 2015
[b1]Amit Sharma:
The Interplay of Personal Preference and Social Influence in Sharing Networks. Cornell University, USA, 2015
Journal Articles
- 2023
- [j4]Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan:
Machine Explanations and Human Understanding. Trans. Mach. Learn. Res. 2023 (2023) - 2019
- [j3]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): 49:1-49:20 (2019) - [j2]Sachin R. Pendse, Kate Niederhoffer, Amit Sharma:
Cross-Cultural Differences in the Use of Online Mental Health Support Forums. Proc. ACM Hum. Comput. Interact. 3(CSCW): 67:1-67:29 (2019) - 2018
- [j1]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): 36-44 (2018)
Conference and Workshop Papers
- 2023
- [c49]Parikshit Bansal, Amit Sharma:
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers. ACL (1) 2023: 2271-2287 - [c48]Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan:
Machine Explanations and Human Understanding. FAccT 2023: 1 - [c47]Jivat Neet Kaur, Emre Kiciman, Amit Sharma:
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization. ICLR 2023 - [c46]Abhinav Kumar, Amit Deshpande, Amit Sharma:
Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations. NeurIPS 2023 - 2022
- [c45]Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma:
Matching Learned Causal Effects of Neural Networks with Domain Priors. ICML 2022: 10676-10696 - [c44]Abhinav Kumar, Chenhao Tan, Amit Sharma:
Probing Classifiers are Unreliable for Concept Removal and Detection. NeurIPS 2022 - [c43]Saloni Dash, Vineeth N. Balasubramanian, Amit Sharma:
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals. WACV 2022: 3879-3888 - 2021
- [c42]Naman Goel, Alfonso Amayuelas, Amit Deshpande, Amit Sharma:
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective. AAAI 2021: 7564-7573 - [c41]Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma:
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. AIES 2021: 652-663 - [c40]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: 545:1-545:16 - [c39]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: 273-288 - [c38]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: 213-217 - [c37]Divyat Mahajan, Shruti Tople, Amit Sharma:
Domain Generalization using Causal Matching. ICML 2021: 7313-7324 - [c36]Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman:
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. WSDM 2021: 409-417 - 2020
- [c35]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: 1-7 - [c34]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: 1-14 - [c33]Amit Sharma, Emre Kiciman:
Causal Inference and Counterfactual Reasoning. COMAD/CODS 2020: 369-370 - [c32]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: 254-264 - [c31]Ramaravind Kommiya Mothilal, Amit Sharma, Chenhao Tan:
Explaining machine learning classifiers through diverse counterfactual explanations. FAT* 2020: 607-617 - [c30]Shruti Tople, Amit Sharma, Aditya Nori:
Alleviating Privacy Attacks via Causal Learning. ICML 2020: 9537-9547 - [c29]Koustuv Saha, Amit Sharma:
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities. ICWSM 2020: 590-601 - [c28]Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma:
Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms. ICWSM 2020: 614-625 - [c27]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: 2832-2838 - [c26]Taisa Kushner, Amit Sharma:
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums. WWW 2020: 2906-2912 - 2019
- [c25]Yada Pruksachatkun, Sachin R. Pendse, Amit Sharma:
Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums. CHI 2019: 64 - [c24]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: 257-261 - [c23]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: 22-36 - [c22]Ramaravind Kommiya Mothilal, Amulya Yadav, Amit Sharma:
Optimizing peer referrals for public awareness using contextual bandits. COMPASS 2019: 74-85 - [c21]Karn Dubey, Palash Gupta, Rachna Shriwas, Gayatri Gulvady, Amit Sharma:
Learnings from deploying a voice-based social platform for people with disability. COMPASS 2019: 111-121 - [c20]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: 2430-2438 - [c19]Emre Kiciman, Amit Sharma:
Causal Inference and Counterfactual Reasoning (3hr Tutorial). WSDM 2019: 828-829 - 2017
- [c18]Mathias Lécuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins:
Harvesting Randomness to Optimize Distributed Systems. HotNets 2017: 178-184 - [c17]Michael D. Ekstrand, Amit Sharma:
FATREC Workshop on Responsible Recommendation. RecSys 2017: 382-383 - [c16]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: 626-633 - 2016
- [c15]Amit Sharma, Dan Cosley:
Distinguishing between Personal Preferences and Social Influence in Online Activity Feeds. CSCW 2016: 1089-1101 - [c14]Benjamin Shulman, Amit Sharma, Dan Cosley:
Predictability of Popularity: Gaps between Prediction and Understanding. ICWSM 2016: 348-357 - [c13]Travis Martin, Jake M. Hofman, Amit Sharma, Ashton Anderson, Duncan J. Watts:
Exploring Limits to Prediction in Complex Social Systems. WWW 2016: 683-694 - [c12]Samuel Barbosa, Dan Cosley, Amit Sharma, Roberto M. Cesar Jr.:
Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand Behavior. WWW 2016: 829-841 - 2015
- [c11]Amit Sharma, Dan Cosley:
Studying and Modeling the Connection between People's Preferences and Content Sharing. CSCW 2015: 1246-1257 - [c10]Amit Sharma, Jake M. Hofman, Duncan J. Watts:
Estimating the Causal Impact of Recommendation Systems from Observational Data. EC 2015: 453-470 - 2014
- [c9]Amit Sharma:
Modeling the effect of people's preferences and social forces on adopting and sharing items. RecSys 2014: 421-424 - 2013
- [c8]Amit Sharma:
PopCore: a system for network-centric recommendation. CSCW Companion 2013: 31-34 - [c7]Amit Sharma, Mevlana Gemici, Dan Cosley:
Friends, Strangers, and the Value of Ego Networks for Recommendation. ICWSM 2013 - [c6]Priyankar Ghosh, Amit Sharma, Partha Pratim Chakrabarti, Pallab Dasgupta:
Algorithms for Generating Ordered Solutions for Explicit AND/OR Structures : Extended Abstract. IJCAI 2013: 3156-3160 - [c5]Amit Sharma:
A Research Platform for Recommendation within Social Networks. RSWeb@RecSys 2013 - [c4]Amit Sharma, Baoshi Yan:
Pairwise learning in recommendation: experiments with community recommendation on linkedin. RecSys 2013: 193-200 - [c3]Amit Sharma, Dan Cosley:
Do social explanations work?: studying and modeling the effects of social explanations in recommender systems. WWW 2013: 1133-1144 - 2011
- [c2]Vimmi Jaiswal, Amit Sharma, Akshat Verma:
ReComp: QoS-aware recursive service composition at minimum cost. Integrated Network Management 2011: 225-232 - [c1]Amit Sharma, Dan Cosley:
Network-Centric Recommendation: Personalization with and in Social Networks. SocialCom/PASSAT 2011: 282-289
Editorship
- 2022
- [e2]Engineer Bainomugisha, Waylon Brunette, Nicola Dell, Amit Sharma:
COMPASS '22: ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, Seattle, WA, USA, 29 June 2022 - 1 July 2022. ACM 2022, ISBN 978-1-4503-9347-8 [contents] - 2016
- [e1]Ido Guy, Amit Sharma:
Proceedings of the Poster Track of the 10th ACM Conference on Recommender Systems (RecSys 2016), Boston, USA, September 17, 2016. CEUR Workshop Proceedings 1688, CEUR-WS.org 2016 [contents]
Informal and Other Publications
- 2024
- [i45]Pragya Srivastava, Satvik Golechha, Amit Deshpande, Amit Sharma:
NICE: To Optimize In-Context Examples or Not? CoRR abs/2402.06733 (2024) - 2023
- [i44]Emre Kiciman, Robert Ness, Amit Sharma, Chenhao Tan:
Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. CoRR abs/2305.00050 (2023) - [i43]Parikshit Bansal, Amit Sharma:
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers. CoRR abs/2305.16863 (2023) - [i42]Abbavaram Gowtham Reddy, Saketh Bachu, Saloni Dash, Charchit Sharma, Amit Sharma, Vineeth N. Balasubramanian:
Rethinking Counterfactual Data Augmentation Under Confounding. CoRR abs/2305.18183 (2023) - [i41]Abhinav Kumar, Amit Deshpande, Amit Sharma:
Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes. CoRR abs/2306.11072 (2023) - [i40]Parikshit Bansal, Amit Sharma:
Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost. CoRR abs/2306.15766 (2023) - [i39]Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma:
Causal Inference Using LLM-Guided Discovery. CoRR abs/2310.15117 (2023) - [i38]Jake M. Hofman, Angelos Chatzimparmpas, Amit Sharma, Duncan J. Watts, Jessica Hullman:
Pre-registration for Predictive Modeling. CoRR abs/2311.18807 (2023) - 2022
- [i37]Tomas Geffner, Javier Antorán, 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 abs/2202.02195 (2022) - [i36]Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan:
Machine Explanations and Human Understanding. CoRR abs/2202.04092 (2022) - [i35]Jivat Neet Kaur, Emre Kiciman, Amit Sharma:
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization. CoRR abs/2206.07837 (2022) - [i34]Abhinav Kumar, Chenhao Tan, Amit Sharma:
Probing Classifiers are Unreliable for Concept Removal and Detection. CoRR abs/2207.04153 (2022) - [i33]Parikshit Bansal, Yashoteja Prabhu, Emre Kiciman, Amit Sharma:
Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems. CoRR abs/2210.10636 (2022) - [i32]Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian:
Counterfactual Generation Under Confounding. CoRR abs/2210.12368 (2022) - 2021
- [i31]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 abs/2101.03989 (2021) - [i30]Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople:
Causally Constrained Data Synthesis for Private Data Release. CoRR abs/2105.13144 (2021) - [i29]Amit Sharma, Vasilis Syrgkanis, Cheng Zhang, Emre Kiciman:
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions. CoRR abs/2108.13518 (2021) - [i28]Divyat Mahajan, Shruti Tople, Amit Sharma:
The Connection between Out-of-Distribution Generalization and Privacy of ML Models. CoRR abs/2110.03369 (2021) - [i27]Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins:
Sayer: Using Implicit Feedback to Optimize System Policies. CoRR abs/2110.14874 (2021) - [i26]Abbavaram Gowtham Reddy, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Amit Sharma:
Causal Regularization Using Domain Priors. CoRR abs/2111.12490 (2021) - [i25]Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis:
Omitted Variable Bias in Machine Learned Causal Models. CoRR abs/2112.13398 (2021) - 2020
- [i24]Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma:
Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms. CoRR abs/2004.04999 (2020) - [i23]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 abs/2004.10270 (2020) - [i22]Taisa Kushner, Amit Sharma:
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums. CoRR abs/2004.10330 (2020) - [i21]Divyat Mahajan, Shruti Tople, Amit Sharma:
Domain Generalization using Causal Matching. CoRR abs/2006.07500 (2020) - [i20]Saloni Dash, Amit Sharma:
Counterfactual Generation and Fairness Evaluation Using Adversarially Learned Inference. CoRR abs/2009.08270 (2020) - [i19]Amit Sharma, Emre Kiciman:
DoWhy: An End-to-End Library for Causal Inference. CoRR abs/2011.04216 (2020) - [i18]Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma:
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. CoRR abs/2011.04917 (2020) - [i17]Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman:
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. CoRR abs/2011.05877 (2020) - [i16]Naman Goel, Alfonso Amayuelas, Amit Deshpande, Amit Sharma:
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective. CoRR abs/2012.11448 (2020) - 2019
- [i15]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 abs/1902.01506 (2019) - [i14]Ramaravind Kommiya Mothilal, Amit Sharma, Chenhao Tan:
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations. CoRR abs/1905.07697 (2019) - [i13]Arpita Biswas, Siddharth Barman, Amit Deshpande, Amit Sharma:
Quantifying Infra-Marginality and Its Trade-off with Group Fairness. CoRR abs/1909.00982 (2019) - [i12]Shruti Tople, Amit Sharma, Aditya Nori:
Alleviating Privacy Attacks via Causal Learning. CoRR abs/1909.12732 (2019) - [i11]Divyat Mahajan, Chenhao Tan, Amit Sharma:
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers. CoRR abs/1912.03277 (2019) - 2017
- [i10]Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz:
Auditing Search Engines for Differential Satisfaction Across Demographics. CoRR abs/1705.10689 (2017) - 2016
- [i9]Travis Martin, Jake M. Hofman, Amit Sharma, Ashton Anderson, Duncan J. Watts:
Exploring limits to prediction in complex social systems. CoRR abs/1602.01013 (2016) - [i8]Samuel Barbosa, Dan Cosley, Amit Sharma, Roberto M. Cesar Jr.:
Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand Behavior. CoRR abs/1603.07025 (2016) - [i7]Benjamin Shulman, Amit Sharma, Dan Cosley:
Predictability of Popularity: Gaps between Prediction and Understanding. CoRR abs/1603.09436 (2016) - [i6]Amit Sharma, Dan Cosley:
Distinguishing between Personal Preferences and Social Influence in Online Activity Feeds. CoRR abs/1604.01105 (2016) - [i5]Amit Sharma, Jake M. Hofman, Duncan J. Watts:
Split-door criterion for causal identification: Automatic search for natural experiments. CoRR abs/1611.09414 (2016) - 2015
- [i4]Amit Sharma, Jake M. Hofman, Duncan J. Watts:
Estimating the Causal Impact of Recommendation Systems from Observational Data. CoRR abs/1510.05569 (2015) - 2014
- [i3]Amit Sharma, Dan Cosley:
Studying and Modeling the Connection between People's Preferences and Content Sharing. CoRR abs/1412.1424 (2014) - 2013
- [i2]Amit Sharma, Dan Cosley:
Do Social Explanations Work? Studying and Modeling the Effects of Social Explanations in Recommender Systems. CoRR abs/1304.3405 (2013) - [i1]Amit Sharma, Mevlana Gemici, Dan Cosley:
Friends, Strangers, and the Value of Ego Networks for Recommendation. CoRR abs/1304.4837 (2013)
Coauthor Index
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