Badanidiyuru, Ashwinkumar

9 publications

UAI 2024 Generalization and Learnability in Multiple Instance Regression Kushal Chauhan, Rishi Saket, Lorne Applebaum, Ashwinkumar Badanidiyuru, Chandan Giri, Aravindan Raghuveer

ICLR 2024 Learning from Aggregate Responses: Instance Level Versus Bag Level Loss Functions Adel Javanmard, Lin Chen, Vahab Mirrokni, Ashwinkumar Badanidiyuru, Gang Fu

ICMLW 2023 Follow-Ups Also Matter: Improving Contextual Bandits via Post-Serving Contexts Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru, Haifeng Xu

NeurIPS 2020 Submodular Maximization Through Barrier Functions Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi, Jan Vondrak

ICML 2016 Fast Constrained Submodular Maximization: Personalized Data Summarization Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi

NeurIPS 2015 Distributed Submodular Cover: Succinctly Summarizing Massive Data Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause

AAAI 2015 Lazier than Lazy Greedy Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause

COLT 2014 Resourceful Contextual Bandits Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins

COLT 2014 Robust Multi-Objective Learning with Mentor Feedback Alekh Agarwal, Ashwinkumar Badanidiyuru, Miroslav Dudík, Robert E. Schapire, Aleksandrs Slivkins