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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)

An Analysis of Convex Relaxations for MAP Estimation NeurIPS 2007 A neural network implementing optimal state estimation based on dynamic spike train decoding NeurIPS 2007 A New View of Automatic Relevance Determination NeurIPS 2007 An Implicit Time-Stepping Method for Multibody Systems with Intermittent Contact RSS 2007 An in-silico Neural Model of Dynamic Routing through Neuronal Coherence NeurIPS 2007 An online Hebbian learning rule that performs Independent Component Analysis NeurIPS 2007 Anytime Induction of Cost-sensitive Trees NeurIPS 2007 Anytime Learning of Decision Trees JMLR 2007 A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians JMLR 2007 A Randomized Algorithm for Large Scale Support Vector Learning NeurIPS 2007 A Risk Minimization Principle for a Class of Parzen Estimators NeurIPS 2007 A Spectral Regularization Framework for Multi-Task Structure Learning NeurIPS 2007 A Stochastic Algorithm for Feature Selection in Pattern Recognition JMLR 2007 A Tree Parameterization for Efficiently Computing Maximum Likelihood Maps using Gradient Descent RSS 2007 Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions JMLR 2007 A Unified Near-Optimal Estimator For Dimension Reduction in l_α (0<α≤ 2) Using Stable Random Projections NeurIPS 2007 Bayes-Adaptive POMDPs NeurIPS 2007 Bayesian Agglomerative Clustering with Coalescents NeurIPS 2007 Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms NeurIPS 2007 Bayesian Co-Training NeurIPS 2007 Bayesian Inference for Spiking Neuron Models with a Sparsity Prior NeurIPS 2007 Bayesian Policy Learning with Trans-Dimensional MCMC NeurIPS 2007 Bayesian Quadratic Discriminant Analysis JMLR 2007 Better than least squares: comparison of objective functions for estimating linear-nonlinear models NeurIPS 2007 Blind channel identification for speech dereverberation using l1-norm sparse learning NeurIPS 2007