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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)

Reparameterization Gradient for Non-differentiable Models NeurIPS 2018 Reparameterizing the Birkhoff Polytope for Variational Permutation Inference AISTATS 2018 Representation Balancing MDPs for Off-policy Policy Evaluation NeurIPS 2018 Representations of Bayesian networks by low-rank models PGM 2018 Representing and Learning High Dimensional Data With the Optimal Transport Map From a Probabilistic Viewpoint CVPR 2018 Representing Social Media Users for Sarcasm Detection EMNLP 2018 Reproducing and Regularizing the SCRN Model COLING 2018 Repulsion Loss: Detecting Pedestrians in a Crowd CVPR 2018 Residual Connections Encourage Iterative Inference ICLR 2018 Residual Loss Prediction: Reinforcement Learning With No Incremental Feedback ICLR 2018 Residual Unfairness in Fair Machine Learning from Prejudiced Data ICML 2018 ResNet with one-neuron hidden layers is a Universal Approximator NeurIPS 2018 Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes NeurIPS 2018 Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression COLT 2018 Rethinking Feature Distribution for Loss Functions in Image Classification CVPR 2018 Revealing Common Statistical Behaviors in Heterogeneous Populations ICML 2018 Reverse Iterative Volume Sampling for Linear Regression JMLR 2018 Revisiting Decomposable Submodular Function Minimization with Incidence Relations NeurIPS 2018 Reviving and Improving Recurrent Back-Propagation ICML 2018 Reward Estimation for Variance Reduction in Deep Reinforcement Learning CoRL 2018 Reward Maximization Under Uncertainty: Leveraging Side-Observations on Networks JMLR 2018 Ridge Regression and Provable Deterministic Ridge Leverage Score Sampling NeurIPS 2018 Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis AISTATS 2018 Ring Loss: Convex Feature Normalization for Face Recognition CVPR 2018 RLlib: Abstractions for Distributed Reinforcement Learning ICML 2018