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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Multiple Operator-valued Kernel Learning NeurIPS 2012 Multiresolution analysis on the symmetric group NeurIPS 2012 Multiresolution Gaussian Processes NeurIPS 2012 Multi-Stage Multi-Task Feature Learning NeurIPS 2012 Multi-Task Averaging NeurIPS 2012 Near-Optimal Algorithms for Online Matrix Prediction COLT 2012 Near-optimal Differentially Private Principal Components NeurIPS 2012 Near-Optimal MAP Inference for Determinantal Point Processes NeurIPS 2012 New Bounds for Learning Intervals with Implications for Semi-Supervised Learning COLT 2012 Newton-Like Methods for Sparse Inverse Covariance Estimation NeurIPS 2012 No Internal Regret via Neighborhood Watch AISTATS 2012 Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics JMLR 2012 Nonconvex Penalization Using Laplace Exponents and Concave Conjugates NeurIPS 2012 Non-parametric Approximate Dynamic Programming via the Kernel Method NeurIPS 2012 Nonparametric Estimation of Conditional Information and Divergences AISTATS 2012 Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction NeurIPS 2012 Nonparametric Reduced Rank Regression NeurIPS 2012 Nonparanormal Belief Propagation (NPNBP) NeurIPS 2012 No-Regret Algorithms for Unconstrained Online Convex Optimization NeurIPS 2012 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NeurIPS 2012 Oger: Modular Learning Architectures For Large-Scale Sequential Processing JMLR 2012 On Average Reward Policy Evaluation in Infinite-State Partially Observable Systems AISTATS 2012 On Bayesian Upper Confidence Bounds for Bandit Problems AISTATS 2012 On Estimation and Selection for Topic Models AISTATS 2012 On Lifting the Gibbs Sampling Algorithm NeurIPS 2012