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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 Bayesian Approach for Policy Learning from Trajectory Preference Queries NeurIPS 2012 A Case Study on Meta-Generalising: A Gaussian Processes Approach JMLR 2012 Accelerated Training for Matrix-norm Regularization: A Boosting Approach NeurIPS 2012 Accuracy at the Top NeurIPS 2012 A Characterization of Scoring Rules for Linear Properties COLT 2012 A Comparison of the Lasso and Marginal Regression JMLR 2012 A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems COLT 2012 A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation NeurIPS 2012 Active Comparison of Prediction Models NeurIPS 2012 Active Learning of Model Evidence Using Bayesian Quadrature NeurIPS 2012 Active Learning of Multi-Index Function Models NeurIPS 2012 Activized Learning: Transforming Passive to Active with Improved Label Complexity JMLR 2012 Adaptive MCMC with Bayesian Optimization AISTATS 2012 Adaptive Metropolis with Online Relabeling AISTATS 2012 Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions NeurIPS 2012 A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification AISTATS 2012 A Distributable and Computation-flexible Assignment Algorithm: From Local Task Swapping to Global Optimality RSS 2012 A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation NeurIPS 2012 A Family of MCMC Methods on Implicitly Defined Manifolds AISTATS 2012 Affine Independent Variational Inference NeurIPS 2012 Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks AISTATS 2012 A General Framework for Structured Sparsity via Proximal Optimization AISTATS 2012 A Geometric Approach to Sample Compression JMLR 2012 A Geometric take on Metric Learning NeurIPS 2012 AIC and BIC based approaches for SVM parameter value estimation with RBF kernels ACML 2012