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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)

Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models NeurIPS 2012 Forward Basis Selection for Sparse Approximation over Dictionary AISTATS 2012 Fully Bayesian inference for neural models with negative-binomial spiking NeurIPS 2012 Fused sparsity and robust estimation for linear models with unknown variance NeurIPS 2012 Gaussian Processes for time-marked time-series data AISTATS 2012 GenDeR: A Generic Diversified Ranking Algorithm NeurIPS 2012 Generalization Bounds for Domain Adaptation NeurIPS 2012 Generalization Bounds for Online Learning Algorithms with Pairwise Loss Functions COLT 2012 Generalized Optimal Reverse Prediction AISTATS 2012 Generic Methods for Optimization-Based Modeling AISTATS 2012 glm-ie: Generalised Linear Models Inference & Estimation Toolbox JMLR 2012 Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins NeurIPS 2012 Gradient-based kernel method for feature extraction and variable selection NeurIPS 2012 Gradient Weights help Nonparametric Regressors NeurIPS 2012 Graphical Models via Generalized Linear Models NeurIPS 2012 Hamming Distance Metric Learning NeurIPS 2012 Hierarchical Optimistic Region Selection driven by Curiosity NeurIPS 2012 High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion JMLR 2012 High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods AISTATS 2012 High-Dimensional Structured Feature Screening Using Binary Markov Random Fields AISTATS 2012 Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints NeurIPS 2012 How Prior Probability Influences Decision Making: A Unifying Probabilistic Model NeurIPS 2012 How They Vote: Issue-Adjusted Models of Legislative Behavior NeurIPS 2012 Identifiability and Unmixing of Latent Parse Trees NeurIPS 2012 Imitation Learning by Coaching NeurIPS 2012