Sohini Upadhyay

25 papers A* 6A 2B 1C 1Misc 2Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	"It just requires so much more creativity": Barriers and Workarounds to Gathering Information for AI Contestation. CHI Sohini Upadhyay, Dasha Pruss, Alicia DeVrio, Krzysztof Z. Gajos, Naveena Karusala
2025	A	`conf`	Counterfactual Explanations May Not Be the Best Algorithmic Recourse Approach. IUI Sohini Upadhyay, Himabindu Lakkaraju, Krzysztof Z. Gajos
2024	—	`conf`	From Stem to Stern: Contestability Along AI Value Chains. CSCW Companion Agathe Balayn, Yulu Pi, David Gray Widder, Kars Alfrink, Mireia Yurrita, Sohini Upadhyay, Naveena Karusala, Henrietta Lyons, Cagatay Turkay, Christelle Tessono, Blair Attard-Frost, Ujwal Gadiraju
2024	J	`jnl`	From Stem to Stern: Contestability Along AI Value Chains. CoRR Agathe Balayn, Yulu Pi, David Gray Widder, Kars Alfrink, Mireia Yurrita, Sohini Upadhyay, Naveena Karusala, Henrietta Lyons, Cagatay Turkay, Christelle Tessono, Blair Attard-Frost, Ujwal Gadiraju
2024	A*	`conf`	Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services. CHI Naveena Karusala, Sohini Upadhyay, Rajesh Veeraraghavan, Krzysztof Z. Gajos
2022	A	`conf`	Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis. AISTATS Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju
2022	C	`conf`	Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations. AIES Jessica Dai, Sohini Upadhyay, Ulrich Aïvodji, Stephen H. Bach, Himabindu Lakkaraju
2022	J	`jnl`	Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations. CoRR Jessica Dai, Sohini Upadhyay, Ulrich Aïvodji, Stephen H. Bach, Himabindu Lakkaraju
2022	B	`conf`	Linear Upper Confident Bound with Missing Reward: Online Learning with Less Data. IJCNN Djallel Bouneffouf, Sohini Upadhyay, Yasaman Khazaeni
2022	J	`jnl`	Metric Elicitation; Moving from Theory to Practice. CoRR Safinah Ali, Sohini Upadhyay, Gaurush Hiranandani, Elena L. Glassman, Oluwasanmi Koyejo
2021	Misc	`conf`	Double-Linear Thompson Sampling for Context-Attentive Bandits. ICASSP Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish
2021	J	`jnl`	Extending LIME for Business Process Automation. CoRR Sohini Upadhyay, Vatche Isahagian, Vinod Muthusamy, Yara Rizk
2021	J	`jnl`	On the Connections between Counterfactual Explanations and Adversarial Examples. CoRR Martin Pawelczyk, Shalmali Joshi, Chirag Agarwal, Sohini Upadhyay, Himabindu Lakkaraju
2021	A*	`conf`	Toward Optimal Solution for the Context-Attentive Bandit Problem. IJCAI Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Irina Rish, Yasaman Khazaeni
2021	Misc	`conf`	Toward Skills Dialog Orchestration with Online Learning. ICASSP Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Mayank Agarwal, Yasaman Khazaeni, Irina Rish
2021	A*	`conf`	Towards Robust and Reliable Algorithmic Recourse. NeurIPS Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju
2021	J	`jnl`	Towards Robust and Reliable Algorithmic Recourse. CoRR Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju
2021	A*	`conf`	Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. ICML Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju
2021	J	`jnl`	Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. CoRR Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Zhiwei Steven Wu, Himabindu Lakkaraju
2021	J	`jnl`	What will it take to generate fairness-preserving explanations? CoRR Jessica Dai, Sohini Upadhyay, Stephen H. Bach, Himabindu Lakkaraju
2020	J	`jnl`	Contextual Bandit with Missing Rewards. CoRR Djallel Bouneffouf, Sohini Upadhyay, Yasaman Khazaeni
2020	J	`jnl`	Double-Linear Thompson Sampling for Context-Attentive Bandits. CoRR Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish
2020	J	`jnl`	Online Semi-Supervised Learning with Bandit Feedback. CoRR Sohini Upadhyay, Mikhail Yurochkin, Mayank Agarwal, Yasaman Khazaeni, Djallel Bouneffouf
2020	A*	`conf`	TraceHub - A Platform to Bridge the Gap between State-of-the-Art Time-Series Analytics and Datasets. AAAI Shubham Agarwal, Christian Muise, Mayank Agarwal, Sohini Upadhyay, Zilu Tang, Zhongshen Zeng, Yasaman Khazaeni
2019	J	`jnl`	A Bandit Approach to Posterior Dialog Orchestration Under a Budget. CoRR Sohini Upadhyay, Mayank Agarwal, Djallel Bouneffouf, Yasaman Khazaeni