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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)

Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel NeurIPS 2022 Disentangling Uncertainty in Machine Translation Evaluation EMNLP 2022 Dist2Cycle: A Simplicial Neural Network for Homology Localization AAAI 2022 Distilling Governing Laws and Source Input for Dynamical Systems from Videos IJCAI 2022 Distinguishing Learning Rules with Brain Machine Interfaces NeurIPS 2022 Distinguishing Relational Pattern Languages With a Small Number of Short Strings ALT 2022 Distinguishing rule and exemplar-based generalization in learning systems ICML 2022 DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems AAAI 2022 Distributed adversarial training to robustify deep neural networks at scale UAI 2022 Distributed Bootstrap for Simultaneous Inference Under High Dimensionality JMLR 2022 Distributed Distributionally Robust Optimization with Non-Convex Objectives NeurIPS 2022 Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems NeurIPS 2022 Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space NeurIPS 2022 Distributed Learning of Finite Gaussian Mixtures JMLR 2022 Distributed Learning with Strategic Users: A Repeated Game Approach AAAI 2022 Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees NeurIPS 2022 Distributed Neural Network Control with Dependability Guarantees: a Compositional Port-Hamiltonian Approach L4DC 2022 Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning ACL 2022 Distributed Online Convex Optimization with Compressed Communication NeurIPS 2022 Distributed Online Learning for Joint Regret with Communication Constraints ALT 2022 Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity NeurIPS 2022 Distributed Randomized Sketching Kernel Learning AAAI 2022 Distributed Sparse Multicategory Discriminant Analysis AISTATS 2022 Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima JMLR 2022 Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters L4DC 2022