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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
352
828
3,646
5,854
2000
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Papers (including subtopics)

Transformers on Markov data: Constant depth suffices NeurIPS 2024 Transformers, parallel computation, and logarithmic depth ICML 2024 Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot ICML 2024 Transformers Represent Belief State Geometry in their Residual Stream NeurIPS 2024 Transformer verbatim in-context retrieval across time and scale CoNLL 2024 TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression AISTATS 2024 Transitional Uncertainty with Layered Intermediate Predictions ICML 2024 Transition Constrained Bayesian Optimization via Markov Decision Processes NeurIPS 2024 Translation Equivariant Transformer Neural Processes ICML 2024 Transport meets Variational Inference: Controlled Monte Carlo Diffusions ICLR 2024 TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction NAACL 2024 Treatment Effects Estimation By Uniform Transformer ICLR 2024 Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness NeurIPS 2024 Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization AAAI 2024 TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing NeurIPS 2024 Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence ICML 2024 Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression AISTATS 2024 Truncated Variance Reduced Value Iteration NeurIPS 2024 Trustless Audits without Revealing Data or Models ICML 2024 Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness AAAI 2024 Trust Regions for Explanations via Black-Box Probabilistic Certification ICML 2024 Trustworthy Actionable Perturbations ICML 2024 Truthfulness of Calibration Measures NeurIPS 2024 Truth Table Net: Scalable, Compact & Verifiable Neural Networks with a Dual Convolutional Small Boolean Circuit Networks Form IJCAI 2024 TSDS: Data Selection for Task-Specific Model Finetuning NeurIPS 2024