On Learnability wih Computable Learners. - Sushant Agarwal; Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner; Ruth Urner (ALT, 2020)

Classification Confidence Scores with Point-wise Guarantees. - Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner (SafeAI@AAAI, 2021)

Open Problem: Are all VC-classes CPAC learnable? - Sushant Agarwal; Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner; Ruth Urner (COLT, 2021)

Identifying regions of trusted predictions. - Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner; Ruth Urner (UAI, 2021)

Impossibility results for fair representations. - Tosca Lechner; Shai Ben-David; Sushant Agarwal; Nivasini Ananthakrishnan (CoRR, 2021)

Delegating Data Collection in Decentralized Machine Learning. - Nivasini Ananthakrishnan; Stephen Bates; Michael I. Jordan; Nika Haghtalab (AISTATS, 2024)

Privacy Can Arise Endogenously in an Economic System with Learning Agents. - Nivasini Ananthakrishnan; Tiffany Ding; Mariel A. Werner; Sai Praneeth Karimireddy; Michael I. Jordan (FORC, 2024)

Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions. - Nivasini Ananthakrishnan; Nika Haghtalab; Chara Podimata; Kunhe Yang (NeurIPS, 2024)

Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interaction. - Nivasini Ananthakrishnan; Nika Haghtalab; Chara Podimata; Kunhe Yang (CoRR, 2024)