Papers
Online Learning Without Prior Information
Ashok Cutkosky, Kwabena Boahen
Tight Bounds for Bandit Combinatorial Optimization
Alon Cohen, Tamir Hazan, Tomer Koren
Thresholding Based Outlier Robust PCA
Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli
Towards Instance Optimal Bounds for Best Arm Identification
Lijie Chen, Jian Li, Mingda Qiao
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration
Lijie Chen, Anupam Gupta, Jian Li et al.
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile et al.
Multi-Observation Elicitation
Sebastian Casalaina-Martin, Rafael Frongillo, Tom Morgan et al.
Testing Bayesian Networks
Clement L. Canonne, Ilias Diakonikolas, Daniel M. Kane et al.
Learning Disjunctions of Predicates
Nader H. Bshouty, Dana Drachsler-Cohen, Martin Vechev et al.
Rates of estimation for determinantal point processes
Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet et al.
Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo
Nicolas Brosse, Alain Durmus, Éric Moulines et al.
Efficient Co-Training of Linear Separators under Weak Dependence
Avrim Blum, Yishay Mansour
The Sample Complexity of Optimizing a Convex Function
Eric Balkanski, Yaron Singer
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems
Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik et al.
Computationally Efficient Robust Sparse Estimation in High Dimensions
Sivaraman Balakrishnan, Simon S. Du, Jerry Li et al.
The Price of Selection in Differential Privacy
Mitali Bafna, Jonathan Ullman
Efficient PAC Learning from the Crowd
Pranjal Awasthi, Avrim Blum, Nika Haghtalab et al.
Correspondence retrieval
Alexandr Andoni, Daniel Hsu, Kevin Shi et al.
Homotopy Analysis for Tensor PCA
Anima Anandkumar, Yuan Deng, Rong Ge et al.
Thompson Sampling for the MNL-Bandit
Shipra Agrawal, Vashist Avadhanula, Vineet Goyal et al.
Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons
Arpit Agarwal, Shivani Agarwal, Sepehr Assadi et al.
Corralling a Band of Bandit Algorithms
Alekh Agarwal, Haipeng Luo, Behnam Neyshabur et al.
Open Problem: Meeting Times for Learning Random Automata
Benjamin Fish, Lev Reyzin
Open Problem: First-Order Regret Bounds for Contextual Bandits
Alekh Agarwal, Akshay Krishnamurthy, John Langford et al.
Preface: Conference on Learning Theory (COLT), 2017
Satyen Kale, Ohad Shamir