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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)

A data-driven model of acoustic speech intelligibility for optimization-based models of speech production Interspeech 2024 A data-driven Riccati equation L4DC 2024 Ad Auctions for LLMs via Retrieval Augmented Generation NeurIPS 2024 AdaZeta: Adaptive Zeroth-Order Tensor-Train Adaption for Memory-Efficient Large Language Models Fine-Tuning EMNLP 2024 Additive smoothing error in backward variational inference for general state-space models JMLR 2024 Addressing Bias in Online Selection with Limited Budget of Comparisons NeurIPS 2024 Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning ICLR 2024 A Decoding Algorithm for Length-Control Summarization Based on Directed Acyclic Transformers EMNLP 2024 A deep learning approach for distributed aggregative optimization with users’ Feedback L4DC 2024 A De-singularity Subgradient Approach for the Extended Weber Location Problem IJCAI 2024 A differentiable brain simulator bridging brain simulation and brain-inspired computing ICLR 2024 A Differentiable Integer Linear Programming Solver for Explanation-Based Natural Language Inference COLING 2024 A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing ICML 2024 A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization ICML 2024 A distributional simplicity bias in the learning dynamics of transformers NeurIPS 2024 A Divide and Conquer Approach for Solving Structural Causal Models PGM 2024 AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models ICLR 2024 Adjusted Wasserstein Distributionally Robust Estimator in Statistical Learning JMLR 2024 ADOPT: Modified Adam Can Converge with Any β_2 with the Optimal Rate NeurIPS 2024 A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization ICML 2024 A Doubly Robust Approach to Sparse Reinforcement Learning AISTATS 2024 ADR-X: ANN-Assisted Wireless Link Rate Adaptation for Compute-Constrained Embedded Gaming Devices NSDI 2024 AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion ICML 2024 A Dual Approach to Imitation Learning from Observations with Offline Datasets CoRL 2024 Advancing Adversarial Suffix Transfer Learning on Aligned Large Language Models EMNLP 2024