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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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'25

Papers (including subtopics)

Rethinking Independent Cross-Entropy Loss For Graph-Structured Data ICML 2024 Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds ICLR 2024 Rethinking LLM Memorization through the Lens of Adversarial Compression NeurIPS 2024 Rethinking Loss Functions for Fact Verification EACL 2024 Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models NeurIPS 2024 Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity NeurIPS 2024 Rethinking Momentum Knowledge Distillation in Online Continual Learning ICML 2024 Rethinking Multi-domain Generalization with A General Learning Objective CVPR 2024 Rethinking Optimal Transport in Offline Reinforcement Learning NeurIPS 2024 Rethinking Optimization and Architecture for Tiny Language Models ICML 2024 Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution NeurIPS 2024 Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz NeurIPS 2024 Rethinking Peculiar Images by Diffusion Models: Revealing Local Minima’s Role AAAI 2024 Rethinking Propagation for Unsupervised Graph Domain Adaptation AAAI 2024 Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization EMNLP 2024 Rethinking the Capacity of Graph Neural Networks for Branching Strategy NeurIPS 2024 Rethinking the Effectiveness of Graph Classification Datasets in Benchmarks for Assessing GNNs IJCAI 2024 Rethinking the Flat Minima Searching in Federated Learning ICML 2024 Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks NeurIPS 2024 Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability ICLR 2024 Rethinking the Soft Conflict Pseudo Boolean Constraint on MaxSAT Local Search Solvers IJCAI 2024 Rethinking the Spatial Inconsistency in Classifier-Free Diffusion Guidance CVPR 2024 Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms ICLR 2024 Rethinking the Uniformity Metric in Self-Supervised Learning ICLR 2024 Rethinking Transformers in Solving POMDPs ICML 2024