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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)

MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID CVPR 2023 MT Metrics Correlate with Human Ratings of Simultaneous Speech Translation ACL 2023 MTR: A Dataset Fusing Inductive, Deductive, and Defeasible Reasoning ACL 2023 MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks ICML 2023 Multi-Agent Automated Machine Learning CVPR 2023 Multi-Agent Best Arm Identification with Private Communications ICML 2023 Multi-Agent congestion cost minimization with linear function approximations AISTATS 2023 Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive Inference AISTATS 2023 Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic masking ACL 2023 Multicalibration as Boosting for Regression ICML 2023 Multiclass Boosting: Simple and Intuitive Weak Learning Criteria NeurIPS 2023 Multiclass Online Learning and Uniform Convergence COLT 2023 Multi-Consensus Decentralized Accelerated Gradient Descent JMLR 2023 Multi-Dataset Co-Training with Sharpness-Aware Optimization for Audio Anti-spoofing Interspeech 2023 Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning ICML 2023 Multi-Fidelity Bayesian Optimization with Unreliable Information Sources AISTATS 2023 Multi-Fidelity Multi-Armed Bandits Revisited NeurIPS 2023 Multi-Layer Neural Networks as Trainable Ladders of Hilbert Spaces ICML 2023 Multi-Level Wavelet Mapping Correlation for Statistical Dependence Measurement: Methodology and Performance AAAI 2023 Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions NeurIPS 2023 Multi-Objective GFlowNets ICML 2023 Multi-Objective Online Learning ICLR 2023 Multi-objective Optimization-based Selection for Quality-Diversity by Non-surrounded-dominated Sorting IJCAI 2023 Multi-objective optimization via equivariant deep hypervolume approximation ICLR 2023 Multi-Objective Population Based Training ICML 2023