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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)

Common Diffusion Noise Schedules and Sample Steps Are Flawed WACV 2024 Communication Bounds for the Distributed Experts Problem NeurIPS 2024 Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates AISTATS 2024 Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits AAAI 2024 Communication Efficient Distributed Newton Method over Unreliable Networks AAAI 2024 Communication Efficient Distributed Training with Distributed Lion NeurIPS 2024 Communication-Efficient Federated Group Distributionally Robust Optimization NeurIPS 2024 Communication-Efficient Federated Learning with Accelerated Client Gradient CVPR 2024 Communication-Efficient Federated Learning With Data and Client Heterogeneity AISTATS 2024 Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates ICLR 2024 Community detection in the hypergraph stochastic block model and reconstruction on hypertrees COLT 2024 Commutative Scaling of Width and Depth in Deep Neural Networks JMLR 2024 Compact Language Models via Pruning and Knowledge Distillation NeurIPS 2024 Compact Optimality Verification for Optimization Proxies ICML 2024 Compact Proofs of Model Performance via Mechanistic Interpretability NeurIPS 2024 Compare without Despair: Reliable Preference Evaluation with Generation Separability EMNLP 2024 Comparing Comparators in Generalization Bounds AISTATS 2024 Comparing Neighbors Together Makes it Easy: Jointly Comparing Multiple Candidates for Efficient and Effective Retrieval EMNLP 2024 Complementary-Contradictory Feature Regularization Against Multimodal Overfitting WACV 2024 Complexity Matters: Feature Learning in the Presence of Spurious Correlations ICML 2024 Complexity of Neural Network Training and ETR: Extensions with Effectively Continuous Functions AAAI 2024 Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints AISTATS 2024 Complex Logical Query Answering by Calibrating Knowledge Graph Completion Models ACL 2024 Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities ICLR 2024 Compositional Curvature Bounds for Deep Neural Networks ICML 2024