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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)

Learning Fourier Sparse Set Functions AISTATS 2012
Efficient and Exact MAP-MRF Inference using Branch and Bound AISTATS 2012
Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness AISTATS 2012
On Estimation and Selection for Topic Models AISTATS 2012
Lifted Variable Elimination with Arbitrary Constraints AISTATS 2012
Structured Output Learning with High Order Loss Functions AISTATS 2012
A Bayesian Analysis of the Radioactive Releases of Fukushima AISTATS 2012
Learning from Weak Teachers AISTATS 2012
Krylov Subspace Descent for Deep Learning AISTATS 2012
Bayesian Group Factor Analysis AISTATS 2012
Generalized Optimal Reverse Prediction AISTATS 2012
Statistical Optimization in High Dimensions AISTATS 2012
Perturbation based Large Margin Approach for Ranking AISTATS 2012
Forward Basis Selection for Sparse Approximation over Dictionary AISTATS 2012
Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers AISTATS 2012
An Autoregressive Approach to Nonparametric Hierarchical Dependent Modeling AISTATS 2012
Sparse Additive Machine AISTATS 2012
Beta-Negative Binomial Process and Poisson Factor Analysis AISTATS 2012
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation AISTATS 2012
(weak) Calibration is Computationally Hard COLT 2012
Learning Valuation Functions COLT 2012
Unified Algorithms for Online Learning and Competitive Analysis COLT 2012
Online Optimization with Gradual Variations COLT 2012
The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators COLT 2012
PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012