Amit Sharma

Orcid: 0000-0002-2086-3191

Affiliations:
  • Microsoft Research, Bangalore, India
  • Cornell University, Ithaca, NY, USA (PhD 2015)
  • IIT Kharagpur, India (former)


According to our database1, Amit Sharma authored at least 74 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
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Article 
PhD thesis 
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Online presence:

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Bibliography

2024
NICE: To Optimize In-Context Examples or Not?
CoRR, 2024

2023
Machine Explanations and Human Understanding.
Trans. Mach. Learn. Res., 2023

Pre-registration for Predictive Modeling.
CoRR, 2023

Causal Inference Using LLM-Guided Discovery.
CoRR, 2023

Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost.
CoRR, 2023

Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes.
CoRR, 2023

Rethinking Counterfactual Data Augmentation Under Confounding.
CoRR, 2023

Causal Reasoning and Large Language Models: Opening a New Frontier for Causality.
CoRR, 2023

Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Counterfactual Generation Under Confounding.
CoRR, 2022

Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems.
CoRR, 2022

Deep End-to-end Causal Inference.
CoRR, 2022

Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Probing Classifiers are Unreliable for Concept Removal and Detection.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Matching Learned Causal Effects of Neural Networks with Domain Priors.
Proceedings of the International Conference on Machine Learning, 2022

2021
Omitted Variable Bias in Machine Learned Causal Models.
CoRR, 2021

Causal Regularization Using Domain Priors.
CoRR, 2021

The Connection between Out-of-Distribution Generalization and Privacy of ML Models.
CoRR, 2021

DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions.
CoRR, 2021

Causally Constrained Data Synthesis for Private Data Release.
CoRR, 2021

Technology Readiness Levels for Machine Learning Systems.
CoRR, 2021

Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions.
Proceedings of the WSDM '21, 2021

Domain Generalization using Causal Matching.
Proceedings of the 38th International Conference on Machine Learning, 2021

MINDNOTES : A Mobile Platform to enable users to break stigma around mental health and connect with therapists.
Proceedings of the Companion Publication of the 2021 ACM Conference on Computer Supported Cooperative Work and Social Computing, 2021

Sayer: Using Implicit Feedback to Optimize System Policies.
Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021

"Can I Not Be Suicidal on a Sunday?": Understanding Technology-Mediated Pathways to Mental Health Support.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
DoWhy: An End-to-End Library for Causal Inference.
CoRR, 2020

Counterfactual Generation and Fairness Evaluation Using Adversarially Learned Inference.
CoRR, 2020

Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi.
Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms.
Proceedings of the Fourteenth International AAAI Conference on Web and Social Media, 2020

Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities.
Proceedings of the Fourteenth International AAAI Conference on Web and Social Media, 2020

Alleviating Privacy Attacks via Causal Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Explaining machine learning classifiers through diverse counterfactual explanations.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Using Mobile Airtime Credits to Incentivize Learning, Sharing and Survey Response: Experiences from the Field.
Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies, 2020

Causal Inference and Counterfactual Reasoning.
Proceedings of the CoDS-COMAD 2020: 7th ACM IKDD CoDS and 25th COMAD, 2020

"Like Shock Absorbers": Understanding the Human Infrastructures of Technology-Mediated Mental Health Support.
Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

Facilitating Media Distribution with Monetary Incentives.
Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020

2019
Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns.
Proc. ACM Hum. Comput. Interact., 2019

Cross-Cultural Differences in the Use of Online Mental Health Support Forums.
Proc. ACM Hum. Comput. Interact., 2019

Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers.
CoRR, 2019

Quantifying Infra-Marginality and Its Trade-off with Group Fairness.
CoRR, 2019

Causal Inference and Counterfactual Reasoning (3hr Tutorial).
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Mental health in the global south: challenges and opportunities in HCI for development.
Proceedings of the Conference on Computing & Sustainable Societies, 2019

Optimizing peer referrals for public awareness using contextual bandits.
Proceedings of the Conference on Computing & Sustainable Societies, 2019

Learnings from deploying a voice-based social platform for people with disability.
Proceedings of the Conference on Computing & Sustainable Societies, 2019

Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness.
Proceedings of the Companion Publication of the 2019 ACM Conference on Computer Supported Cooperative Work and Social Computing, 2019

Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums.
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

2018
Reports of the Workshops Held at the 2018 International AAAI Conference on Web and Social Media.
AI Mag., 2018

2017
Auditing Search Engines for Differential Satisfaction Across Demographics.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017

FATREC Workshop on Responsible Recommendation.
Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Harvesting Randomness to Optimize Distributed Systems.
Proceedings of the 16th ACM Workshop on Hot Topics in Networks, Palo Alto, CA, USA, 2017

2016
Split-door criterion for causal identification: Automatic search for natural experiments.
CoRR, 2016

Exploring Limits to Prediction in Complex Social Systems.
Proceedings of the 25th International Conference on World Wide Web, 2016

Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand Behavior.
Proceedings of the 25th International Conference on World Wide Web, 2016

Predictability of Popularity: Gaps between Prediction and Understanding.
Proceedings of the Tenth International Conference on Web and Social Media, 2016

Distinguishing between Personal Preferences and Social Influence in Online Activity Feeds.
Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 2016

2015
The Interplay of Personal Preference and Social Influence in Sharing Networks.
PhD thesis, 2015

Estimating the Causal Impact of Recommendation Systems from Observational Data.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Studying and Modeling the Connection between People's Preferences and Content Sharing.
Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, 2015

2014
Modeling the effect of people's preferences and social forces on adopting and sharing items.
Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

2013
Do social explanations work?: studying and modeling the effects of social explanations in recommender systems.
Proceedings of the 22nd International World Wide Web Conference, 2013

Pairwise learning in recommendation: experiments with community recommendation on linkedin.
Proceedings of the Seventh ACM Conference on Recommender Systems, 2013

A Research Platform for Recommendation within Social Networks.
Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), 2013

Algorithms for Generating Ordered Solutions for Explicit AND/OR Structures : Extended Abstract.
Proceedings of the IJCAI 2013, 2013

Friends, Strangers, and the Value of Ego Networks for Recommendation.
Proceedings of the Seventh International Conference on Weblogs and Social Media, 2013

PopCore: a system for network-centric recommendation.
Proceedings of the Computer Supported Cooperative Work, 2013

2011
Network-Centric Recommendation: Personalization with and in Social Networks.
Proceedings of the PASSAT/SocialCom 2011, Privacy, 2011

ReComp: QoS-aware recursive service composition at minimum cost.
Proceedings of the 12th IFIP/IEEE International Symposium on Integrated Network Management, 2011


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