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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)

Blending Data-Driven Priors in Dynamic Games RSS 2024 Blind Image Restoration via Fast Diffusion Inversion NeurIPS 2024 BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models NeurIPS 2024 Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares ICML 2024 BlockBoost: Scalable and Efficient Blocking through Boosting AISTATS 2024 Block-Level Goal Recognition Design AAAI 2024 Block Sparse Bayesian Learning: A Diversified Scheme NeurIPS 2024 BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation ICML 2024 BMRS: Bayesian Model Reduction for Structured Pruning NeurIPS 2024 BOBA: Byzantine-Robust Federated Learning with Label Skewness AISTATS 2024 BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling NeurIPS 2024 Boosted Conformal Prediction Intervals NeurIPS 2024 Boosting Adversarial Training via Fisher-Rao Norm-based Regularization CVPR 2024 Boosting CTC-based ASR using inter-layer attention-based CTC loss Interspeech 2024 Boosting Diffusion Models with an Adaptive Momentum Sampler IJCAI 2024 Boosting Diffusion Models with Moving Average Sampling in Frequency Domain CVPR 2024 Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning NeurIPS 2024 Boosting Offline Optimizers with Surrogate Sensitivity ICML 2024 Boosting Order-Preserving and Transferability for Neural Architecture Search: a Joint Architecture Refined Search and Fine-tuning Approach CVPR 2024 Boosting Text-to-Video Generative Model with MLLMs Feedback NeurIPS 2024 Boosting Vision-Language Models with Transduction NeurIPS 2024 Bootstrap aggregation and confidence measures to improve time series causal discovery CLeaR 2024 Bootstrapped Pre-training with Dynamic Identifier Prediction for Generative Retrieval ACL 2024 BotChat: Evaluating LLMs’ Capabilities of Having Multi-Turn Dialogues NAACL 2024 BOtied: Multi-objective Bayesian optimization with tied multivariate ranks ICML 2024