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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)

Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability L4DC 2020 Controllability of Control Argumentation Frameworks IJCAI 2020 Controllable Orthogonalization in Training DNNs CVPR 2020 Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics ICML 2020 ConvBERT: Improving BERT with Span-based Dynamic Convolution NeurIPS 2020 Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling AISTATS 2020 Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization ICML 2020 Convergence of Gradient Methods on Bilinear Zero-Sum Games ICLR 2020 Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters NeurIPS 2020 Convergence of Sparse Variational Inference in Gaussian Processes Regression JMLR 2020 Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions JMLR 2020 Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization ACML 2020 Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference AISTATS 2020 Convergence Rates of Variational Inference in Sparse Deep Learning ICML 2020 Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections JMLR 2020 Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer Games ICML 2020 Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels JMLR 2020 Convex Calibrated Surrogates for the Multi-Label F-Measure ICML 2020 Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable Models AISTATS 2020 Convex optimization based on global lower second-order models NeurIPS 2020 Convex Programming for Estimation in Nonlinear Recurrent Models JMLR 2020 Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space ICML 2020 Co-Occurrence Estimation from Aggregated Data with Auxiliary Information AAAI 2020 Cooperative Initialization based Deep Neural Network Training WACV 2020 Cooperative Multi-Agent Bandits with Heavy Tails ICML 2020