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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)

Less is More: Parameter-Efficient Selection of Intermediate Tasks for Transfer Learning EMNLP 2024 Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often! ICML 2024 Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation ICLR 2024 LESS: Selecting Influential Data for Targeted Instruction Tuning ICML 2024 Let's Verify Step by Step ICLR 2024 Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models EMNLP 2024 Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification ICML 2024 Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals NeurIPS 2024 Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning ICLR 2024 Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks AISTATS 2024 Leveraging Drift to Improve Sample Complexity of Variance Exploding Diffusion Models NeurIPS 2024 Leveraging Estimated Transferability Over Human Intuition for Model Selection in Text Ranking EMNLP 2024 Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning L4DC 2024 Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design ICLR 2024 Leveraging Large Language Models for NLG Evaluation: Advances and Challenges EMNLP 2024 Leveraging Optimization for Adaptive Attacks on Image Watermarks ICLR 2024 Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures AISTATS 2024 Leveraging partial stragglers within gradient coding NeurIPS 2024 Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference ICML 2024 Leveraging Uncertainty Estimates To Improve Classifier Performance ICLR 2024 LG-FGAD: An Effective Federated Graph Anomaly Detection Framework IJCAI 2024 LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch NeurIPS 2024 Lie Group Decompositions for Equivariant Neural Networks ICLR 2024 Lifelong Event Detection via Optimal Transport EMNLP 2024 Light Schrödinger Bridge ICLR 2024