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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)

Approximation of hidden Markov models by mixtures of experts with application to particle filtering AISTATS 2010
A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection AISTATS 2010
Bayesian structure discovery in Bayesian networks with less space AISTATS 2010
Identifying Cause and Effect on Discrete Data using Additive Noise Models AISTATS 2010
REGO: Rank-based Estimation of Renyi Information using Euclidean Graph Optimization AISTATS 2010
Infinite Predictor Subspace Models for Multitask Learning AISTATS 2010
Nonparametric prior for adaptive sparsity AISTATS 2010
Convexity of Proper Composite Binary Losses AISTATS 2010
A Regularization Approach to Nonlinear Variable Selection AISTATS 2010
Approximate parameter inference in a stochastic reaction-diffusion model AISTATS 2010
Active Sequential Learning with Tactile Feedback AISTATS 2010
Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials AISTATS 2010
Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching AISTATS 2010
Dense Message Passing for Sparse Principal Component Analysis AISTATS 2010
Empirical Bernstein Boosting AISTATS 2010
Reduced-Rank Hidden Markov Models AISTATS 2010
On the relation between universality, characteristic kernels and RKHS embedding of measures AISTATS 2010
On the Convergence Properties of Contrastive Divergence AISTATS 2010
Inference and Learning in Networks of Queues AISTATS 2010
Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation AISTATS 2010
HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010
Bayesian Gaussian Process Latent Variable Model AISTATS 2010
A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping AISTATS 2010
State-Space Inference and Learning with Gaussian Processes AISTATS 2010
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures AISTATS 2010