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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)

A Study of Bayesian Neural Network Surrogates for Bayesian Optimization ICLR 2024 A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle ICML 2024 A Study of Parameter Efficient Fine-tuning by Learning to Efficiently Fine-Tune EMNLP 2024 A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning NeurIPS 2024 A Study on the Calibration of In-context Learning NAACL 2024 A Sublinear Adversarial Training Algorithm ICLR 2024 A Surprisingly Simple Continuous-Action POMDP Solver: Lazy Cross-Entropy Search Over Policy Trees AAAI 2024 A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences NeurIPS 2024 A Survey of Learning Criteria Going beyond the Usual Risk (Abstract Reprint) AAAI 2024 A Survey on Multi-player Bandits JMLR 2024 A Survey on Plan Optimization IJCAI 2024 A Swap Relaxation-Based Local Search for the Latin Square Completion Problem IJCAI 2024 A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm NeurIPS 2024 A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers NAACL 2024 Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning ICLR 2024 Asymptotically Optimal and Computationally Efficient Average Treatment Effect Estimation in A/B testing ICML 2024 Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers AISTATS 2024 Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families NeurIPS 2024 Asymptotics of feature learning in two-layer networks after one gradient-step ICML 2024 Asymptotics of Learning with Deep Structured (Random) Features ICML 2024 Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization AISTATS 2024 A Systematic Analysis on the Temporal Generalization of Language Models in Social Media ACL 2024 A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models NAACL 2024 A Tale of Tails: Model Collapse as a Change of Scaling Laws ICML 2024 A Tale of Two Revisions: Summarizing Changes Across Document Versions ACL 2024