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Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo COLT 2017
Rates of estimation for determinantal point processes COLT 2017
Learning Disjunctions of Predicates COLT 2017
Testing Bayesian Networks COLT 2017
Multi-Observation Elicitation COLT 2017
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning COLT 2017
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration COLT 2017
Towards Instance Optimal Bounds for Best Arm Identification COLT 2017
Thresholding Based Outlier Robust PCA COLT 2017
Tight Bounds for Bandit Combinatorial Optimization COLT 2017
Online Learning Without Prior Information COLT 2017
Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent COLT 2017
Depth Separation for Neural Networks COLT 2017
Square Hellinger Subadditivity for Bayesian Networks and its Applications to Identity Testing COLT 2017
Learning Multivariate Log-concave Distributions COLT 2017
Generalization for Adaptively-chosen Estimators via Stable Median COLT 2017
A General Characterization of the Statistical Query Complexity COLT 2017
Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$ COLT 2017
ZigZag: A New Approach to Adaptive Online Learning COLT 2017
High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition COLT 2017
Effective Semisupervised Learning on Manifolds COLT 2017
Reliably Learning the ReLU in Polynomial Time COLT 2017
Fast Rates for Empirical Risk Minimization of Strict Saddle Problems COLT 2017
Nearly-tight VC-dimension bounds for piecewise linear neural networks COLT 2017
Surprising properties of dropout in deep networks COLT 2017