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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)

Does an Efficient Calibrated Forecasting Strategy Exist? COLT 2011
Bounds on Individual Risk for Log-loss Predictors COLT 2011
A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011
Minimax Algorithm for Learning Rotations COLT 2011
Missing Information Impediments to Learnability COLT 2011
Bayesian Generalized Kernel Mixed Models JMLR 2011
Training SVMs Without Offset JMLR 2011
Logistic Stick-Breaking Process JMLR 2011
Online Learning in Case of Unbounded Losses Using Follow the Perturbed Leader Algorithm JMLR 2011
A Bayesian Approximation Method for Online Ranking JMLR 2011
Models of Cooperative Teaching and Learning JMLR 2011
Operator Norm Convergence of Spectral Clustering on Level Sets JMLR 2011
Approximate Marginals in Latent Gaussian Models JMLR 2011
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning JMLR 2011
Variable Sparsity Kernel Learning JMLR 2011
Parameter Screening and Optimisation for ILP using Designed Experiments JMLR 2011
Information, Divergence and Risk for Binary Experiments JMLR 2011
Sparse Linear Identifiable Multivariate Modeling JMLR 2011
-Norm Multiple Kernel Learning JMLR 2011
Differentially Private Empirical Risk Minimization JMLR 2011
The Indian Buffet Process: An Introduction and Review JMLR 2011
DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model JMLR 2011
Locally Defined Principal Curves and Surfaces JMLR 2011
Better Algorithms for Benign Bandits JMLR 2011
A Family of Simple Non-Parametric Kernel Learning Algorithms JMLR 2011