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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
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828
3,646
5,854
2000
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Papers (including subtopics)

AdaLomo: Low-memory Optimization with Adaptive Learning Rate ACL 2024 Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees JMLR 2024 Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps NeurIPS 2024 Adam with model exponential moving average is effective for nonconvex optimization NeurIPS 2024 Adaptation Odyssey in LLMs: Why Does Additional Pretraining Sometimes Fail to Improve? EMNLP 2024 Adapted Weighted Aggregation in Federated Learning AAAI 2024 Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate ICML 2024 Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models NeurIPS 2024 Adaptive Accompaniment with ReaLchords ICML 2024 Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning ICML 2024 Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression AISTATS 2024 Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization NeurIPS 2024 Adaptive Anytime Multi-Agent Path Finding Using Bandit-Based Large Neighborhood Search AAAI 2024 Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach AISTATS 2024 Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling ECCV 2024 Adaptive Compression in Federated Learning via Side Information AISTATS 2024 Adaptive Conformal Inference by Betting ICML 2024 Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism ICLR 2024 Adaptive Exploration for Data-Efficient General Value Function Evaluations NeurIPS 2024 Adaptive Feature-based Low-Rank Compression of Large Language Models via Bayesian Optimization EMNLP 2024 Adaptive Federated Learning with Auto-Tuned Clients ICLR 2024 Adaptive Federated Minimax Optimization with Lower Complexities AISTATS 2024 Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations ICML 2024 Adaptive Group Personalization for Federated Mutual Transfer Learning ICML 2024 Adaptive Hardness Negative Sampling for Collaborative Filtering AAAI 2024