Sohini Upadhyay

Orcid: 0009-0009-3314-0839

According to our database1, Sohini Upadhyay authored at least 18 papers between 2019 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
From Stem to Stern: Contestability Along AI Value Chains.
Proceedings of the Companion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing, 2024

Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services.
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

2022
Metric Elicitation; Moving from Theory to Practice.
CoRR, 2022

Linear Upper Confident Bound with Missing Reward: Online Learning with Less Data.
Proceedings of the International Joint Conference on Neural Networks, 2022

Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations.
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021
Extending LIME for Business Process Automation.
CoRR, 2021

What will it take to generate fairness-preserving explanations?
CoRR, 2021

On the Connections between Counterfactual Explanations and Adversarial Examples.
CoRR, 2021

Towards Robust and Reliable Algorithmic Recourse.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Toward Optimal Solution for the Context-Attentive Bandit Problem.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Towards the Unification and Robustness of Perturbation and Gradient Based Explanations.
Proceedings of the 38th International Conference on Machine Learning, 2021

Double-Linear Thompson Sampling for Context-Attentive Bandits.
Proceedings of the IEEE International Conference on Acoustics, 2021

Toward Skills Dialog Orchestration with Online Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Online Semi-Supervised Learning with Bandit Feedback.
CoRR, 2020

Contextual Bandit with Missing Rewards.
CoRR, 2020

TraceHub - A Platform to Bridge the Gap between State-of-the-Art Time-Series Analytics and Datasets.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
A Bandit Approach to Posterior Dialog Orchestration Under a Budget.
CoRR, 2019


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