Lower bounds for two-sample structural change detection in ising and Gaussian models. - Aditya Gangrade; Bobak Nazer; Venkatesh Saligrama (Allerton, 2017)

Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds. - Aditya Gangrade; Bobak Nazer; Venkatesh Saligrama (ICASSP, 2018)

Testing Changes in Communities for the Stochastic Block Model. - Aditya Gangrade; Praveen Venkatesh; Bobak Nazer; Venkatesh Saligrama (CoRR, 2018)

Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models. - Aditya Gangrade; Praveen Venkatesh; Bobak Nazer; Venkatesh Saligrama (NeurIPS, 2019)

Budget Learning via Bracketing. - Durmus Alp Emre Acar; Aditya Gangrade; Venkatesh Saligrama (AISTATS, 2020)

Piecewise Linear Regression via a Difference of Convex Functions. - Ali Siahkamari; Aditya Gangrade; Brian Kulis; Venkatesh Saligrama (ICML, 2020)

Limits on Testing Structural Changes in Ising Models. - Aditya Gangrade; Bobak Nazer; Venkatesh Saligrama (NeurIPS, 2020)

Selective Classification via One-Sided Prediction. - Aditya Gangrade; Anil Kag; Venkatesh Saligrama (AISTATS, 2021)

Online Selective Classification with Limited Feedback. - Aditya Gangrade; Anil Kag; Ashok Cutkosky; Venkatesh Saligrama (NeurIPS, 2021)

Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. - Tianrui Chen; Aditya Gangrade; Venkatesh Saligrama (ICML, 2022)

A Doubly Optimistic Strategy for Safe Linear Bandits. - Tianrui Chen; Aditya Gangrade; Venkatesh Saligrama (CoRR, 2022)

Scaffolding a Student to Instill Knowledge. - Anil Kag; Durmus Alp Emre Acar; Aditya Gangrade; Venkatesh Saligrama (ICLR, 2023)

Efficient Edge Inference by Selective Query. - Anil Kag; Igor Fedorov; Aditya Gangrade; Paul N. Whatmough; Venkatesh Saligrama (ICLR, 2023)

Counterfactually Comparing Abstaining Classifiers. - Yo Joong Choe; Aditya Gangrade; Aaditya Ramdas (NeurIPS, 2023)

Safe Linear Bandits over Unknown Polytopes. - Aditya Gangrade; Tianrui Chen; Venkatesh Saligrama (COLT, 2024)

Testing the Feasibility of Linear Programs with Bandit Feedback. - Aditya Gangrade; Aditya Gopalan; Venkatesh Saligrama; Clayton Scott (ICML, 2024)

Label Noise: Ignorance Is Bliss. - Yilun Zhu 002; Jianxin Zhang; Aditya Gangrade; Clayton Scott (NeurIPS, 2024)

SPARC: Score Prompting and Adaptive Fusion for Zero-Shot Multi-Label Recognition in Vision-Language Models. - Kevin Miller; Aditya Gangrade; Samarth Mishra; Kate Saenko; Venkatesh Saligrama (CVPR, 2025)

Universal Inference Meets Random Projections: A Scalable Test for Log-Concavity. - Robin Dunn; Aditya Gangrade; Larry A. Wasserman; Aaditya Ramdas (J. Comput. Graph. Stat., 2025)

Constrained Linear Thompson Sampling. - Aditya Gangrade; Venkatesh Saligrama (CoRR, 2025)