| 2017 | A General Characterization of the Statistical Query Complexity. Vitaly Feldman |
| 2017 | A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics. Yuchen Zhang, Percy Liang, Moses Charikar |
| 2017 | A Second-order Look at Stability and Generalization. Andreas Maurer |
| 2017 | A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints. Bin Hu, Peter Seiler, Anders Rantzer |
| 2017 | Adaptivity to Noise Parameters in Nonparametric Active Learning. Andrea Locatelli, Alexandra Carpentier, Samory Kpotufe |
| 2017 | Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning. Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile, Sébastien Gerchinovitz |
| 2017 | An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits. Yevgeny Seldin, Gábor Lugosi |
| 2017 | Bandits with Movement Costs and Adaptive Pricing. Tomer Koren, Roi Livni, Yishay Mansour |
| 2017 | Computationally Efficient Robust Sparse Estimation in High Dimensions. Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh |
| 2017 | Corralling a Band of Bandit Algorithms. Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, Robert E. Schapire |
| 2017 | Correspondence retrieval. Alexandr Andoni, Daniel J. Hsu, Kevin Shi, Xiaorui Sun |
| 2017 | Depth Separation for Neural Networks. Amit Daniely |
| 2017 | Effective Semisupervised Learning on Manifolds. Amir Globerson, Roi Livni, Shai Shalev-Shwartz |
| 2017 | Efficient Co-Training of Linear Separators under Weak Dependence. Avrim Blum, Yishay Mansour |
| 2017 | Efficient PAC Learning from the Crowd. Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour |
| 2017 | Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds. Lijun Zhang, Tianbao Yang, Rong Jin |
| 2017 | Exact tensor completion with sum-of-squares. Aaron Potechin, David Steurer |
| 2017 | Fast Rates for Empirical Risk Minimization of Strict Saddle Problems. Alon Gonen, Shai Shalev-Shwartz |
| 2017 | Fast and robust tensor decomposition with applications to dictionary learning. Tselil Schramm, David Steurer |
| 2017 | Fast rates for online learning in Linearly Solvable Markov Decision Processes. Gergely Neu, Vicenç Gómez |
| 2017 | Fundamental limits of symmetric low-rank matrix estimation. Marc Lelarge, Léo Miolane |
| 2017 | Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent. Arnak S. Dalalyan |
| 2017 | Generalization for Adaptively-chosen Estimators via Stable Median. Vitaly Feldman, Thomas Steinke |
| 2017 | Greed Is Good: Near-Optimal Submodular Maximization via Greedy Optimization. Moran Feldman, Christopher Harshaw, Amin Karbasi |
| 2017 | High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition. David Gamarnik, Ilias Zadik |
| 2017 | Homotopy Analysis for Tensor PCA. Anima Anandkumar, Yuan Deng, Rong Ge, Hossein Mobahi |
| 2017 | Ignoring Is a Bliss: Learning with Large Noise Through Reweighting-Minimization. Daniel Vainsencher, Shie Mannor, Huan Xu |
| 2017 | Inapproximability of VC Dimension and Littlestone's Dimension. Pasin Manurangsi, Aviad Rubinstein |
| 2017 | Learning Disjunctions of Predicates. Nader H. Bshouty, Dana Drachsler-Cohen, Martin T. Vechev, Eran Yahav |
| 2017 | Learning Multivariate Log-concave Distributions. Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2017 | Learning Non-Discriminatory Predictors. Blake E. Woodworth, Suriya Gunasekar, Mesrob I. Ohannessian, Nathan Srebro |
| 2017 | Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons. Arpit Agarwal, Shivani Agarwal, Sepehr Assadi, Sanjeev Khanna |
| 2017 | Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems. Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White |
| 2017 | Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization. Jonathan Scarlett, Ilija Bogunovic, Volkan Cevher |
| 2017 | Matrix Completion from $O(n)$ Samples in Linear Time. David Gamarnik, Quan Li, Hongyi Zhang |
| 2017 | Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch Prox. Jialei Wang, Weiran Wang, Nathan Srebro |
| 2017 | Memoryless Sequences for Differentiable Losses. Rafael M. Frongillo, Andrew B. Nobel |
| 2017 | Mixing Implies Lower Bounds for Space Bounded Learning. Dana Moshkovitz, Michal Moshkovitz |
| 2017 | Multi-Observation Elicitation. Sebastian Casalaina-Martin, Rafael M. Frongillo, Tom Morgan, Bo Waggoner |
| 2017 | Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration. Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang |
| 2017 | Nearly-tight VC-dimension bounds for piecewise linear neural networks. Nick Harvey, Christopher Liaw, Abbas Mehrabian |
| 2017 | Noisy Population Recovery from Unknown Noise. Shachar Lovett, Jiapeng Zhang |
| 2017 | Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis. Maxim Raginsky, Alexander Rakhlin, Matus Telgarsky |
| 2017 | On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities. Alexander Rakhlin, Karthik Sridharan |
| 2017 | On Learning vs. Refutation. Salil P. Vadhan |
| 2017 | On the Ability of Neural Nets to Express Distributions. Holden Lee, Rong Ge, Tengyu Ma, Andrej Risteski, Sanjeev Arora |
| 2017 | Online Learning Without Prior Information. Ashok Cutkosky, Kwabena Boahen |
| 2017 | Open Problem: First-Order Regret Bounds for Contextual Bandits. Alekh Agarwal, Akshay Krishnamurthy, John Langford, Haipeng Luo, Robert E. Schapire |
| 2017 | Open Problem: Meeting Times for Learning Random Automata. Benjamin Fish, Lev Reyzin |
| 2017 | Optimal learning via local entropies and sample compression. Nikita Zhivotovskiy |
| 2017 | Predicting with Distributions. Michael J. Kearns, Zhiwei Steven Wu |
| 2017 | Preface: Conference on Learning Theory (COLT), 2017. Satyen Kale, Ohad Shamir |
| 2017 | Proceedings of the 30th Conference on Learning Theory, COLT 2017, Amsterdam, The Netherlands, 7-10 July 2017 Satyen Kale, Ohad Shamir |
| 2017 | Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes. Lunjia Hu, Ruihan Wu, Tianhong Li, Liwei Wang |
| 2017 | Rates of estimation for determinantal point processes. Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet, John Urschel |
| 2017 | Reliably Learning the ReLU in Polynomial Time. Surbhi Goel, Varun Kanade, Adam R. Klivans, Justin Thaler |
| 2017 | Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities. Jerry Li, Ludwig Schmidt |
| 2017 | Sample complexity of population recovery. Yury Polyanskiy, Ananda Theertha Suresh, Yihong Wu |
| 2017 | Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo. Nicolas Brosse, Alain Durmus, Eric Moulines, Marcelo Pereyra |
| 2017 | Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality. Song Mei, Theodor Misiakiewicz, Andrea Montanari, Roberto Imbuzeiro Oliveira |
| 2017 | Sparse Stochastic Bandits. Joon Kwon, Vianney Perchet, Claire Vernade |
| 2017 | Square Hellinger Subadditivity for Bayesian Networks and its Applications to Identity Testing. Constantinos Daskalakis, Qinxuan Pan |
| 2017 | Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$. Nicolas Flammarion, Francis R. Bach |
| 2017 | Submodular Optimization under Noise. Avinatan Hassidim, Yaron Singer |
| 2017 | Surprising properties of dropout in deep networks. David P. Helmbold, Philip M. Long |
| 2017 | Ten Steps of EM Suffice for Mixtures of Two Gaussians. Constantinos Daskalakis, Christos Tzamos, Manolis Zampetakis |
| 2017 | Testing Bayesian Networks. Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2017 | The Hidden Hubs Problem. Ravindran Kannan, Santosh S. Vempala |
| 2017 | The Price of Selection in Differential Privacy. Mitali Bafna, Jonathan R. Ullman |
| 2017 | The Sample Complexity of Optimizing a Convex Function. Eric Balkanski, Yaron Singer |
| 2017 | The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime. Max Simchowitz, Kevin Jamieson, Benjamin Recht |
| 2017 | Thompson Sampling for the MNL-Bandit. Shipra Agrawal, Vashist Avadhanula, Vineet Goyal, Assaf Zeevi |
| 2017 | Thresholding Based Outlier Robust PCA. Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli |
| 2017 | Tight Bounds for Bandit Combinatorial Optimization. Alon Cohen, Tamir Hazan, Tomer Koren |
| 2017 | Towards Instance Optimal Bounds for Best Arm Identification. Lijie Chen, Jian Li, Mingda Qiao |
| 2017 | Two-Sample Tests for Large Random Graphs Using Network Statistics. Debarghya Ghoshdastidar, Maurilio Gutzeit, Alexandra Carpentier, Ulrike von Luxburg |
| 2017 | ZigZag: A New Approach to Adaptive Online Learning. Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan |