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Publication search results
found 127 matches
- 2020
- Gautam Kamath, Vikrant Singhal, Jonathan R. Ullman:
Private Mean Estimation of Heavy-Tailed Distributions. COLT 2020: 2204-2235 - Srinivasan Parthasarathy:
Adaptive Submodular Maximization under Stochastic Item Costs. COLT 2020: 3133-3151 - Jacob D. Abernethy, Shivani Agarwal:
Conference on Learning Theory 2020: Preface. COLT 2020: 1-2 - Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi:
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit. COLT 2020: 3-40 - Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi:
Distributed Signal Detection under Communication Constraints. COLT 2020: 41-63 - Alekh Agarwal, Sham M. Kakade, Jason D. Lee, Gaurav Mahajan:
Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes. COLT 2020: 64-66 - Alekh Agarwal, Sham M. Kakade, Lin F. Yang:
Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal. COLT 2020: 67-83 - Kwangjun Ahn, Suvrit Sra:
From Nesterov's Estimate Sequence to Riemannian Acceleration. COLT 2020: 84-118 - Noga Alon, Yossi Azar, Danny Vainstein:
Hierarchical Clustering: A 0.585 Revenue Approximation. COLT 2020: 153-162 - Noga Alon, Amos Beimel, Shay Moran, Uri Stemmer:
Closure Properties for Private Classification and Online Prediction. COLT 2020: 119-152 - Ehsan Amid, Manfred K. Warmuth:
Winnowing with Gradient Descent. COLT 2020: 163-182 - Kareem Amin, Matthew Joseph, Jieming Mao:
Pan-Private Uniformity Testing. COLT 2020: 183-218 - C. J. Argue, Anupam Gupta, Guru Guruganesh:
Dimension-Free Bounds for Chasing Convex Functions. COLT 2020: 219-241 - Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan:
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations. COLT 2020: 242-299 - Gérard Ben Arous, Alexander S. Wein, Ilias Zadik:
Free Energy Wells and Overlap Gap Property in Sparse PCA. COLT 2020: 479-482 - Valeriy Avanesov:
Data-driven confidence bands for distributed nonparametric regression. COLT 2020: 300-322 - Pranjal Awasthi, Xue Chen, Aravindan Vijayaraghavan:
Estimating Principal Components under Adversarial Perturbations. COLT 2020: 323-362 - Arturs Backurs, Avrim Blum, Neha Gupta:
Active Local Learning. COLT 2020: 363-390 - James P. Bailey, Gauthier Gidel, Georgios Piliouras:
Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent. COLT 2020: 391-407 - Han Bao, Clayton Scott, Masashi Sugiyama:
Calibrated Surrogate Losses for Adversarially Robust Classification. COLT 2020: 408-451 - Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont:
Complexity Guarantees for Polyak Steps with Momentum. COLT 2020: 452-478 - Guy Blanc, Neha Gupta, Gregory Valiant, Paul Valiant:
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process. COLT 2020: 483-513 - Antonio Blanca, Zongchen Chen, Daniel Stefankovic, Eric Vigoda:
Hardness of Identity Testing for Restricted Boltzmann Machines and Potts models. COLT 2020: 514-529 - Etienne Boursier, Vianney Perchet:
Selfish Robustness and Equilibria in Multi-Player Bandits. COLT 2020: 530-581 - Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy:
Proper Learning, Helly Number, and an Optimal SVM Bound. COLT 2020: 582-609 - Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy:
Sharper Bounds for Uniformly Stable Algorithms. COLT 2020: 610-626 - Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth:
The Gradient Complexity of Linear Regression. COLT 2020: 627-647 - Matthew S. Brennan, Guy Bresler:
Reducibility and Statistical-Computational Gaps from Secret Leakage. COLT 2020: 648-847 - Guy Bresler, Dheeraj Nagaraj:
A Corrective View of Neural Networks: Representation, Memorization and Learning. COLT 2020: 848-901 - Alon Brutzkus, Amit Daniely, Eran Malach:
ID3 Learns Juntas for Smoothed Product Distributions. COLT 2020: 902-915
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