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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)

Limiting fluctuation and trajectorial stability of multilayer neural networks with mean field training NeurIPS 2021 Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings JMLR 2021 Linear and Kernel Classification in the Streaming Model: Improved Bounds for Heavy Hitters NeurIPS 2021 Linear Bandits on Uniformly Convex Sets JMLR 2021 Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients NeurIPS 2021 Linear Convergence of Gradient Methods for Estimating Structured Transition Matrices in High-dimensional Vector Autoregressive Models NeurIPS 2021 Linear Convergent Decentralized Optimization with Compression ICLR 2021 Linear Last-iterate Convergence in Constrained Saddle-point Optimization ICLR 2021 Linear Mode Connectivity in Multitask and Continual Learning ICLR 2021 LinearSpeech: Parallel Text-to-Speech with Linear Complexity Interspeech 2021 Linear Transformers Are Secretly Fast Weight Programmers ICML 2021 Lipschitz Recurrent Neural Networks ICLR 2021 LIRA: Learnable, Imperceptible and Robust Backdoor Attacks ICCV 2021 List-Decodable Mean Estimation in Nearly-PCA Time NeurIPS 2021 List Learning with Attribute Noise AISTATS 2021 Littlestone Classes are Privately Online Learnable NeurIPS 2021 Living Without Beth and Craig: Definitions and Interpolants in Description Logics with Nominals and Role Inclusions AAAI 2021 LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking ACL 2021 Local Competition and Stochasticity for Adversarial Robustness in Deep Learning AISTATS 2021 Local Differential Privacy for Bayesian Optimization AAAI 2021 Local Differential Privacy for Regret Minimization in Reinforcement Learning NeurIPS 2021 LocalGAN: Modeling Local Distributions for Adversarial Response Generation JMLR 2021 Locality defeats the curse of dimensionality in convolutional teacher-student scenarios NeurIPS 2021 Localization, Convexity, and Star Aggregation NeurIPS 2021 Localizing Changes in High-Dimensional Regression Models AISTATS 2021