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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)

Domain Decomposition Approach for Fast Gaussian Process Regression of Large Spatial Data Sets JMLR 2011 Dynamical segmentation of single trials from population neural data NeurIPS 2011 Dynamic Policy Programming with Function Approximation AISTATS 2011 Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons NeurIPS 2011 Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials NeurIPS 2011 Efficient inference in matrix-variate Gaussian models with \iid observation noise NeurIPS 2011 Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression NeurIPS 2011 Efficient Methods for Overlapping Group Lasso NeurIPS 2011 Efficient Offline Communication Policies for Factored Multiagent POMDPs NeurIPS 2011 Efficient Online Learning via Randomized Rounding NeurIPS 2011 Efficient variable selection in support vector machines via the alternating direction method of multipliers AISTATS 2011 EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NeurIPS 2011 Empirical models of spiking in neural populations NeurIPS 2011 Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011 Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011 Estimating beta-mixing coefficients AISTATS 2011 Estimating Diffusion Probability Changes for AsIC-SIS Model from Information Diffusion Results ACML 2011 Estimating Probabilities in Recommendation Systems AISTATS 2011 Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron NeurIPS 2011 Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks AISTATS 2011 Exploiting Variable Stiffness in Explosive Movement Tasks RSS 2011 Expressive Power and Approximation Errors of Restricted Boltzmann Machines NeurIPS 2011 Faithfulness in Chain Graphs: The Gaussian Case AISTATS 2011 Fast b-matching via Sufficient Selection Belief Propagation AISTATS 2011 Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference AISTATS 2011