![[Conference on Learning Theory Logo]](/v65/assets/images/logo-pmlr.svg){kind=logo}
[edit]
Volume 65: Conference on Learning Theory, 7-10 July 2017, Amsterdam, Netherlands
[edit]
Editors: Satyen Kale, Ohad Shamir
Preface: Conference on Learning Theory (COLT), 2017
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1-3
[abs][Download PDF]
Open Problem: First-Order Regret Bounds for Contextual Bandits
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:4-7
[abs][Download PDF]
Open Problem: Meeting Times for Learning Random Automata
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:8-11
[abs][Download PDF]
Corralling a Band of Bandit Algorithms
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:12-38
[abs][Download PDF]
Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:39-75
[abs][Download PDF]
Thompson Sampling for the MNL-Bandit
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:76-78
[abs][Download PDF]
Homotopy Analysis for Tensor PCA
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:79-104
[abs][Download PDF]
Correspondence retrieval
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:105-126
[abs][Download PDF]
Efficient PAC Learning from the Crowd
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:127-150
[abs][Download PDF]
The Price of Selection in Differential Privacy
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:151-168
[abs][Download PDF]
Computationally Efficient Robust Sparse Estimation in High Dimensions
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:169-212
[abs][Download PDF]
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:213-274
[abs][Download PDF]
The Sample Complexity of Optimizing a Convex Function
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:275-301
[abs][Download PDF]
Efficient Co-Training of Linear Separators under Weak Dependence
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:302-318
[abs][Download PDF]
Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:319-342
[abs][Download PDF]
Rates of estimation for determinantal point processes
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:343-345
[abs][Download PDF]
Learning Disjunctions of Predicates
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:346-369
[abs][Download PDF]
Testing Bayesian Networks
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:370-448
[abs][Download PDF]
Multi-Observation Elicitation
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:449-464
[abs][Download PDF]
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:465-481
[abs][Download PDF]
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:482-534
[abs][Download PDF]
Towards Instance Optimal Bounds for Best Arm Identification
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:535-592
[abs][Download PDF]
Thresholding Based Outlier Robust PCA
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:593-628
[abs][Download PDF]
Tight Bounds for Bandit Combinatorial Optimization
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:629-642
[abs][Download PDF]
Online Learning Without Prior Information
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:643-677
[abs][Download PDF]
Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:678-689
[abs][Download PDF]
Depth Separation for Neural Networks
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:690-696
[abs][Download PDF]
Square Hellinger Subadditivity for Bayesian Networks and its Applications to Identity Testing
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:697-703
[abs][Download PDF]
Ten Steps of EM Suffice for Mixtures of Two Gaussians
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:704-710
[abs][Download PDF]
Learning Multivariate Log-concave Distributions
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:711-727
[abs][Download PDF]
Generalization for Adaptively-chosen Estimators via Stable Median
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:728-757
[abs][Download PDF]
Greed Is Good: Near-Optimal Submodular Maximization via Greedy Optimization
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:758-784
[abs][Download PDF]
A General Characterization of the Statistical Query Complexity
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:785-830
[abs][Download PDF]
Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:831-875
[abs][Download PDF]
ZigZag: A New Approach to Adaptive Online Learning
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:876-924
[abs][Download PDF]
Memoryless Sequences for Differentiable Losses
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:925-939
[abs][Download PDF]
Matrix Completion from $O(n)$ Samples in Linear Time
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:940-947
[abs][Download PDF]
High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:948-953
[abs][Download PDF]
Two-Sample Tests for Large Random Graphs Using Network Statistics
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:954-977
[abs][Download PDF]
Effective Semisupervised Learning on Manifolds
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:978-1003
[abs][Download PDF]
Reliably Learning the ReLU in Polynomial Time
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1004-1042
[abs][Download PDF]
Fast Rates for Empirical Risk Minimization of Strict Saddle Problems
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1043-1063
[abs][Download PDF]
Nearly-tight VC-dimension bounds for piecewise linear neural networks
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1064-1068
[abs][Download PDF]
Submodular Optimization under Noise
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1069-1122
[abs][Download PDF]
Surprising properties of dropout in deep networks
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1123-1146
[abs][Download PDF]
Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1147-1156
[abs][Download PDF]
A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1157-1189
[abs][Download PDF]
The Hidden Hubs Problem
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1190-1213
[abs][Download PDF]
Predicting with Distributions
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1214-1241
[abs][Download PDF]
Bandits with Movement Costs and Adaptive Pricing
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1242-1268
[abs][Download PDF]
Sparse Stochastic Bandits
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1269-1270
[abs][Download PDF]
On the Ability of Neural Nets to Express Distributions
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1271-1296
[abs][Download PDF]
Fundamental limits of symmetric low-rank matrix estimation
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1297-1301
[abs][Download PDF]
Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1302-1382
[abs][Download PDF]
Adaptivity to Noise Parameters in Nonparametric Active Learning
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1383-1416
[abs][Download PDF]
Noisy Population Recovery from Unknown Noise
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1417-1431
[abs][Download PDF]
Inapproximability of VC Dimension and Littlestone’s Dimension
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1432-1460
[abs][Download PDF]
A Second-order Look at Stability and Generalization
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1461-1475
[abs][Download PDF]
Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1476-1515
[abs][Download PDF]
Mixing Implies Lower Bounds for Space Bounded Learning
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1516-1566
[abs][Download PDF]
Fast rates for online learning in Linearly Solvable Markov Decision Processes
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1567-1588
[abs][Download PDF]
Sample complexity of population recovery
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1589-1618
[abs][Download PDF]
Exact tensor completion with sum-of-squares
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1619-1673
[abs][Download PDF]
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1674-1703
[abs][Download PDF]
On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1704-1722
[abs][Download PDF]
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1723-1742
[abs][Download PDF]
An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1743-1759
[abs][Download PDF]
Fast and robust tensor decomposition with applications to dictionary learning
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1760-1793
[abs][Download PDF]
The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1794-1834
[abs][Download PDF]
On Learning vs. Refutation
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1835-1848
[abs][Download PDF]
Ignoring Is a Bliss: Learning with Large Noise Through Reweighting-Minimization
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1849-1881
[abs][Download PDF]
Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch Prox
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1882-1919
[abs][Download PDF]
Learning Non-Discriminatory Predictors
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1920-1953
[abs][Download PDF]
Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1954-1979
[abs][Download PDF]
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:1980-2022
[abs][Download PDF]
Optimal learning via local entropies and sample compression
; Proceedings of the 2017 Conference on Learning Theory, PMLR 65:2023-2065
[abs][Download PDF]
subscribe via RSS