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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks ICLR 2020 Pairwise Learning with Differential Privacy Guarantees AAAI 2020 Pan-Private Uniformity Testing COLT 2020 Parabolic Approximation Line Search for DNNs NeurIPS 2020 Parallel AND/OR Search for Marginal MAP AAAI 2020 Parallels Between Phase Transitions and Circuit Complexity? COLT 2020 Parameter-free, Dynamic, and Strongly-Adaptive Online Learning ICML 2020 Parameterised Resource-Bounded ATL AAAI 2020 Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning AAAI 2020 Parameterized Rate-Distortion Stochastic Encoder ICML 2020 Parametric Gaussian Process Regressors ICML 2020 Partial AUC Optimisation Using Recurrent Neural Networks for Music Detection with Limited Training Data Interspeech 2020 Partial Multi-Label Learning with Noisy Label Identification AAAI 2020 Partial Weight Adaptation for Robust DNN Inference CVPR 2020 Particle Filter Recurrent Neural Networks AAAI 2020 Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms JMLR 2020 Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks NeurIPS 2020 pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization IJCAI 2020 PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search ICLR 2020 Peeking Behind the Ordinal Curtain: Improving Distortion via Cardinal Queries AAAI 2020 Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates ICML 2020 PeerNomination: Relaxing Exactness for Increased Accuracy in Peer Selection IJCAI 2020 Pegasus: Tolerating Skewed Workloads in Distributed Storage with In-Network Coherence Directories OSDI 2020 Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets NeurIPS 2020 PEP: Parameter Ensembling by Perturbation NeurIPS 2020