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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)

DeBayes: a Bayesian Method for Debiasing Network Embeddings ICML 2020 Debiased Sinkhorn barycenters ICML 2020 Debiasing Averaged Stochastic Gradient Descent to handle missing values NeurIPS 2020 Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization NeurIPS 2020 Decentralised Learning with Random Features and Distributed Gradient Descent ICML 2020 Decentralized Accelerated Proximal Gradient Descent NeurIPS 2020 Decentralized Deep Learning with Arbitrary Communication Compression ICLR 2020 Decentralized gradient methods: does topology matter? AISTATS 2020 Decentralized Langevin Dynamics for Bayesian Learning NeurIPS 2020 Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis NeurIPS 2020 Decidability and Complexity of Action-Based Temporal Planning over Dense Time AAAI 2020 Deciding Acceptance in Incomplete Argumentation Frameworks AAAI 2020 Decision-Making with Auto-Encoding Variational Bayes NeurIPS 2020 Decision trees as partitioning machines to characterize their generalization properties NeurIPS 2020 Decoding As Dynamic Programming For Recurrent Autoregressive Models ICLR 2020 Decorrelated Clustering with Data Selection Bias IJCAI 2020 Decoupled Greedy Learning of CNNs ICML 2020 Deductive Module Extraction for Expressive Description Logics IJCAI 2020 DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference ACL 2020 Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior AAAI 2020 Deep Differentiable Grasp Planner for High-DOF Grippers RSS 2020 Deep Double Descent: Where Bigger Models and More Data Hurt ICLR 2020 Deep Energy-based Modeling of Discrete-Time Physics NeurIPS 2020 Deep Evidential Regression NeurIPS 2020 Deep Facial Non-Rigid Multi-View Stereo CVPR 2020