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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)

Transformer-Based Language Model Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens EMNLP 2023 Transformer-Based Learned Optimization CVPR 2023 Transformer-based Planning for Symbolic Regression NeurIPS 2023 Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization ICML 2023 Transformer-based World Models Are Happy With 100k Interactions ICLR 2023 Transformer Language Models Handle Word Frequency in Prediction Head ACL 2023 Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars NeurIPS 2023 Transformers as Algorithms: Generalization and Stability in In-context Learning ICML 2023 Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection NeurIPS 2023 Transformers learn through gradual rank increase NeurIPS 2023 Transformers learn to implement preconditioned gradient descent for in-context learning NeurIPS 2023 TranSFormer: Slow-Fast Transformer for Machine Translation ACL 2023 Transformers with Learnable Activation Functions EACL 2023 Transformer Working Memory Enables Regular Language Reasoning And Natural Language Length Extrapolation EMNLP 2023 Transparency at the Source: Evaluating and Interpreting Language Models With Access to the True Distribution EMNLP 2023 Transportation-Inequalities, Lyapunov Stability and Sampling for Dynamical Systems on Continuous State Space L4DC 2023 Transport Elliptical Slice Sampling AISTATS 2023 Transport Reversible Jump Proposals AISTATS 2023 Traversing Between Modes in Function Space for Fast Ensembling ICML 2023 Tree-AMP: Compositional Inference with Tree Approximate Message Passing JMLR 2023 Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters NeurIPS 2023 Tree Learning: Optimal Sample Complexity and Algorithms AAAI 2023 Treepiece: Faster Semantic Parsing via Tree Tokenization EMNLP 2023 Trial matching: capturing variability with data-constrained spiking neural networks NeurIPS 2023 Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs AAAI 2023