Hegde, Nidhi

8 publications

ICML 2025 Connecting Thompson Sampling and UCB: Towards More Efficient Trade-Offs Between Privacy and Regret Bingshan Hu, Zhiming Huang, Tianyue H. Zhang, Mathias Lécuyer, Nidhi Hegde

NeurIPS 2024 Mixture of Nested Experts: Adaptive Processing of Visual Tokens Gagan Jain, Nidhi Hegde, Aditya Kusupati, Arsha Nagrani, Shyamal Buch, Prateek Jain, Anurag Arnab, Sujoy Paul

CoLLAs 2023 Differentially Private Algorithms for Efficient Online Matroid Optimization Kushagra Chandak, Bingshan Hu, Nidhi Hegde

UAI 2023 Optimistic Thompson Sampling-Based Algorithms for Episodic Reinforcement Learning Bingshan Hu, Tianyue H. Zhang, Nidhi Hegde, Mark Schmidt

UAI 2022 Near-Optimal Thompson Sampling-Based Algorithms for Differentially Private Stochastic Bandits Bingshan Hu, Nidhi Hegde

ICLR 2022 Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum Kirby Banman, Garnet Liam Peet-Pare, Nidhi Hegde, Alona Fyshe, Martha White

NeurIPS 2019 Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces Baoxiang Wang, Nidhi Hegde

NeurIPS 2017 Adaptive Active Hypothesis Testing Under Limited Information Fabio Cecchi, Nidhi Hegde