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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)

Distantly-Supervised Joint Extraction with Noise-Robust Learning ACL 2024 Distilling Autoregressive Models to Obtain High-Performance Non-autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed AAAI 2024 DistiLLM: Towards Streamlined Distillation for Large Language Models ICML 2024 DistillSpec: Improving Speculative Decoding via Knowledge Distillation ICLR 2024 DISTMM: Accelerating Distributed Multimodal Model Training NSDI 2024 Distributed Bilevel Optimization with Communication Compression ICML 2024 Distributed Estimation on Semi-Supervised Generalized Linear Model JMLR 2024 Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms JMLR 2024 Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery ICML 2024 Distributed Least Squares in Small Space via Sketching and Bias Reduction NeurIPS 2024 Distributed Manifold Hashing for Image Set Classification and Retrieval AAAI 2024 Distributed on-the-fly control of multi-agent systems with unknown dynamics: Using limited data to obtain near-optimal control L4DC 2024 Distributed-Order Fractional Graph Operating Network NeurIPS 2024 Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification ICML 2024 Distributionally Robust Data Valuation ICML 2024 Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity JMLR 2024 Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions UAI 2024 Distributionally Robust Optimization with Bias and Variance Reduction ICLR 2024 Distributionally Robust Performative Prediction NeurIPS 2024 Distributionally Robust Quickest Change Detection using Wasserstein Uncertainty Sets AISTATS 2024 Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms NeurIPS 2024 Distributional Off-Policy Evaluation for Slate Recommendations AAAI 2024 Distributional Properties of Subword Regularization EMNLP 2024 Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation NeurIPS 2024 Distribution-Aware Data Expansion with Diffusion Models NeurIPS 2024