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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)

A near-optimal algorithm for finite partial-monitoring games against adversarial opponents COLT 2013 An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation ICML 2013 An Enhanced Structure-from-Motion Paradigm Based on the Absolute Dual Quadric and Images of Circular Points ICCV 2013 A New Convex Relaxation for Tensor Completion NeurIPS 2013 An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision CVPR 2013 Annealing between distributions by averaging moments NeurIPS 2013 A Non-parametric Bayesian Network Prior of Human Pose ICCV 2013 An Optimal Policy for Target Localization with Application to Electron Microscopy ICML 2013 A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers ICML 2013 A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions AISTATS 2013 A Plug-in Approach to Neyman-Pearson Classification JMLR 2013 Approachability, fast and slow COLT 2013 Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NeurIPS 2013 Approximate Gaussian process inference for the drift function in stochastic differential equations NeurIPS 2013 Approximate Inference in Collective Graphical Models ICML 2013 Approximate Inference in Continuous Determinantal Processes NeurIPS 2013 Approximate inference in latent Gaussian-Markov models from continuous time observations NeurIPS 2013 Approximating the Permanent with Fractional Belief Propagation JMLR 2013 Approximation properties of DBNs with binary hidden units and real-valued visible units ICML 2013 A Practical Algorithm for Topic Modeling with Provable Guarantees ICML 2013 A Practical Rank-Constrained Eight-Point Algorithm for Fundamental Matrix Estimation CVPR 2013 A Practical Transfer Learning Algorithm for Face Verification ICCV 2013 A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions ICML 2013 A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning ICML 2013 A recursive estimate for the predictive likelihood in a topic model AISTATS 2013