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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)

Efficient Nonparametric Smoothness Estimation NIPS 2016
Sampling for Bayesian Program Learning NIPS 2016
Unifying Count-Based Exploration and Intrinsic Motivation NIPS 2016
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NIPS 2016
Observational-Interventional Priors for Dose-Response Learning NIPS 2016
A Bayesian method for reducing bias in neural representational similarity analysis NIPS 2016
Multistage Campaigning in Social Networks NIPS 2016
Global Optimality of Local Search for Low Rank Matrix Recovery NIPS 2016
Optimistic Bandit Convex Optimization NIPS 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NIPS 2016
Learning in Games: Robustness of Fast Convergence NIPS 2016
Causal Bandits: Learning Good Interventions via Causal Inference NIPS 2016
Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning NIPS 2016
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than $O(1/\epsilon)$ NIPS 2016
Fast Algorithms for Robust PCA via Gradient Descent NIPS 2016
Dimensionality Reduction of Massive Sparse Datasets Using Coresets NIPS 2016
Doubly Convolutional Neural Networks NIPS 2016
Local Minimax Complexity of Stochastic Convex Optimization NIPS 2016
Kronecker Determinantal Point Processes NIPS 2016
Normalized Spectral Map Synchronization NIPS 2016
Error Analysis of Generalized Nyström Kernel Regression NIPS 2016
Regularized Nonlinear Acceleration NIPS 2016
Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning NIPS 2016
DISCO Nets : DISsimilarity COefficients Networks NIPS 2016
Clustering with Bregman Divergences: an Asymptotic Analysis NIPS 2016