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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)

Learning Longer-term Dependencies in RNNs with Auxiliary Losses ICML 2018 Learning Long Term Dependencies via Fourier Recurrent Units ICML 2018 Learning Loop Invariants for Program Verification NeurIPS 2018 Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time ICML 2018 Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances CVPR 2018 Learning One Convolutional Layer with Overlapping Patches ICML 2018 Learning One-hidden-layer Neural Networks with Landscape Design ICLR 2018 Learning Optimal Reserve Price against Non-myopic Bidders NeurIPS 2018 Learning Others' Intentional Models in Multi-Agent Settings Using Interactive POMDPs NeurIPS 2018 Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data NeurIPS 2018 Learning Parametric Closed-Loop Policies for Markov Potential Games ICLR 2018 Learning Priors for Invariance AISTATS 2018 Learning Single-Index Models in Gaussian Space COLT 2018 Learning Sparse Neural Networks through L_0 Regularization ICLR 2018 Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity AISTATS 2018 Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking CVPR 2018 Learning Steerable Filters for Rotation Equivariant CNNs CVPR 2018 Learning Strict Identity Mappings in Deep Residual Networks CVPR 2018 Learning Structural Weight Uncertainty for Sequential Decision-Making AISTATS 2018 Learning the Reward Function for a Misspecified Model ICML 2018 Learning Time/Memory-Efficient Deep Architectures With Budgeted Super Networks CVPR 2018 Learning to Branch ICML 2018 Learning to Converse with Noisy Data: Generation with Calibration IJCAI 2018 Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks MLHC 2018 Learning To Learn Around A Common Mean NeurIPS 2018