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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)

Continual Learning via Sequential Function-Space Variational Inference ICML 2022 Continual Learning with Guarantees via Weight Interval Constraints ICML 2022 Continual Learning with Recursive Gradient Optimization ICLR 2022 Continual Normalization: Rethinking Batch Normalization for Online Continual Learning ICLR 2022 Continual Repeated Annealed Flow Transport Monte Carlo ICML 2022 Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization EMNLP 2022 Continuously Tempered PDMP samplers NeurIPS 2022 Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems ICML 2022 Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 Contraction rates for sparse variational approximations in Gaussian process regression JMLR 2022 Contrastive Conditional Neural Processes CVPR 2022 Contrastive Dual Gating: Learning Sparse Features With Contrastive Learning CVPR 2022 Contrastive Learning for Space-Time Correspondence via Self-Cycle Consistency CVPR 2022 Controllable Factuality in Document-Grounded Dialog Systems Using a Noisy Channel Model EMNLP 2022 Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints NeurIPS 2022 Controlling Epidemic Spread using Probabilistic Diffusion Models on Networks AISTATS 2022 Controlling the Complexity and Lipschitz Constant improves Polynomial Nets ICLR 2022 Convergence Analysis of Linear Coupling with Inexact Proximal Operator UAI 2022 Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings AAAI 2022 Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering ICML 2022 Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum L4DC 2022 Convergence beyond the over-parameterized regime using Rayleigh quotients NeurIPS 2022 Convergence for score-based generative modeling with polynomial complexity NeurIPS 2022 Convergence Guarantees for the Good-Turing Estimator JMLR 2022 Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models PGM 2022