Abhishek Shetty

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 35

Top Topics

Top Venues

Publications

Parikshit Gopalan, Princewill Okoroafor, Prasad Raghavendra, Abhishek Shetty, Mihir Singhal
Omnipredictors for Regression and the Approximate Rank of Convex Functions. CoRR (2024)
Adam Block, Mark Bun, Rathin Desai, Abhishek Shetty, Steven Wu
Oracle-Efficient Differentially Private Learning with Public Data. CoRR (2024)
Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty
Smooth Nash Equilibria: Algorithms and Complexity. ITCS (2024)
Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty
Smooth Nash Equilibria: Algorithms and Complexity. CoRR (2023)
Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
Optimal PAC Bounds Without Uniform Convergence. CoRR (2023)
Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
Adversarial Resilience in Sequential Prediction via Abstention. CoRR (2023)
Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
Adversarial Resilience in Sequential Prediction via Abstention. NeurIPS (2023)
Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty
Smoothed Analysis of Sequential Probability Assignment. CoRR (2023)
Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty
Smoothed Analysis of Sequential Probability Assignment. NeurIPS (2023)
Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
Optimal PAC Bounds without Uniform Convergence. FOCS (2023)
Don Kurian Dennis, Abhishek Shetty, Anish Sevekari, Kazuhito Koishida, Virginia Smith
Progressive Knowledge Distillation: Building Ensembles for Efficient Inference. CoRR (2023)
Don Kurian Dennis, Abhishek Shetty, Anish Prasad Sevekari, Kazuhito Koishida, Virginia Smith
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference. NeurIPS (2023)
Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
The One-Inclusion Graph Algorithm is not Always Optimal. COLT (2023)
Abhishek Shetty, Raaz Dwivedi, Lester Mackey
Distribution Compression in Near-Linear Time. ICLR (2022)
Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
The One-Inclusion Graph Algorithm is not Always Optimal. CoRR (2022)
Nika Haghtalab, Yanjun Han, Abhishek Shetty, Kunhe Yang
Oracle-Efficient Online Learning for Smoothed Adversaries. NeurIPS (2022)
Samuel B. Hopkins, Prasad Raghavendra, Abhishek Shetty
Matrix discrepancy from Quantum communication. STOC (2022)
Nika Haghtalab, Tim Roughgarden, Abhishek Shetty
Smoothed Analysis with Adaptive Adversaries. FOCS (2022)
Nika Haghtalab, Yanjun Han, Abhishek Shetty, Kunhe Yang
Oracle-Efficient Online Learning for Beyond Worst-Case Adversaries. CoRR (2022)
Eshan Chattopadhyay, Jason Gaitonde, Chin Ho Lee, Shachar Lovett, Abhishek Shetty
Fractional Pseudorandom Generators from Any Fourier Level. Computational Complexity Conference (2021)
Nika Haghtalab, Tim Roughgarden, Abhishek Shetty
Smoothed Analysis with Adaptive Adversaries. CoRR (2021)
Abhishek Shetty, Raaz Dwivedi, Lester Mackey
Distribution Compression in Near-linear Time. CoRR (2021)
Samuel B. Hopkins, Prasad Raghavendra, Abhishek Shetty
Matrix Discrepancy from Quantum Communication. CoRR (2021)
Nika Haghtalab, Tim Roughgarden, Abhishek Shetty
Smoothed Analysis with Adaptive Adversaries. FOCS (2021)
Abhishek Panigrahi, Abhishek Shetty, Navin Goyal
Effect of Activation Functions on the Training of Overparametrized Neural Nets. ICLR (2020)
Eshan Chattopadhyay, Jason Gaitonde, Abhishek Shetty
Fractional Pseudorandom Generators from the $k$th Fourier Level. Electron. Colloquium Comput. Complex. 27 (2020)
Eshan Chattopadhyay, Jason Gaitonde, Chin Ho Lee, Shachar Lovett, Abhishek Shetty
Fractional Pseudorandom Generators from Any Fourier Level. CoRR (2020)
Nika Haghtalab, Tim Roughgarden, Abhishek Shetty
Smoothed Analysis of Online and Differentially Private Learning. CoRR (2020)
Nika Haghtalab, Tim Roughgarden, Abhishek Shetty
Smoothed Analysis of Online and Differentially Private Learning. NeurIPS (2020)
Navin Goyal, Abhishek Shetty
Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature. CoRR (2019)
Abhishek Panigrahi, Abhishek Shetty, Navin Goyal
Effect of Activation Functions on the Training of Overparametrized Neural Nets. CoRR (2019)
Navin Goyal, Abhishek Shetty
Non-Gaussian component analysis using entropy methods. STOC (2019)
Sudeep Raja Putta, Abhishek Shetty
Exponential Weights on the Hypercube in Polynomial Time. AISTATS (2019)
Navin Goyal, Abhishek Shetty
Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature. COLT (2019)
Navin Goyal, Abhishek Shetty
Non-Gaussian Component Analysis using Entropy Methods. CoRR (2018)