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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)

Bottleneck-Minimal Indexing for Generative Document Retrieval ICML 2024 Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations JMLR 2024 Boundary Decomposition for Nadir Objective Vector Estimation NeurIPS 2024 Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints ICML 2024 Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs ICML 2024 Bounded robustness in reinforcement learning via lexicographic objectives L4DC 2024 Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty AISTATS 2024 Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments ICLR 2024 Bounding causal effects with leaky instruments UAI 2024 Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data ICML 2024 Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks ICLR 2024 Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension NeurIPS 2024 BPO: Staying Close to the Behavior LLM Creates Better Online LLM Alignment EMNLP 2024 BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning NeurIPS 2024 BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback ICML 2024 BrainBits: How Much of the Brain are Generative Reconstruction Methods Using? NeurIPS 2024 BranchNorm: Robustly Scaling Extremely Deep Transformers ACL 2024 Breadth-First Exploration on Adaptive Grid for Reinforcement Learning ICML 2024 Breaking isometric ties and introducing priors in Gromov-Wasserstein distances AISTATS 2024 Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling EMNLP 2024 Breaking the curse of dimensionality in structured density estimation NeurIPS 2024 Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems AISTATS 2024 Breaking through the learning plateaus of in-context learning in Transformer ICML 2024 Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds JMLR 2024 Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses ICML 2024