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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
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828
3,646
5,854
2000
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Papers (including subtopics)

Decoding Human Language Acquisition: EEG Evidence for Predictive Probabilistic Statistics in Word Segmentation Interspeech 2024 Decoding-time Realignment of Language Models ICML 2024 Decomposable Transformer Point Processes NeurIPS 2024 Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation CVPR 2024 Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems ICLR 2024 DeconfuseTrack: Dealing with Confusion for Multi-Object Tracking CVPR 2024 Deconstructing the Goldilocks Zone of Neural Network Initialization ICML 2024 Decorrelated Variable Importance JMLR 2024 Decoupled Kullback-Leibler Divergence Loss NeurIPS 2024 Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations ICLR 2024 Decoupled Optimisation for Long-Tailed Visual Recognition AAAI 2024 Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks ICML 2024 Decoupling Learning and Decision-Making: Breaking the O(√T) Barrier in Online Resource Allocation with First-Order Methods ICML 2024 Decoupling Semantic Similarity from Spatial Alignment for Neural Networks. NeurIPS 2024 Deep anytime-valid hypothesis testing AISTATS 2024 DeepBern-Nets: Taming the Complexity of Certifying Neural Networks Using Bernstein Polynomial Activations and Precise Bound Propagation AAAI 2024 Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees AAAI 2024 Deep Dependency Networks and Advanced Inference Schemes for Multi-Label Classification AISTATS 2024 DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection NeurIPS 2024 Deep Equilibrium Algorithmic Reasoning NeurIPS 2024 Deep Equilibrium Diffusion Restoration with Parallel Sampling CVPR 2024 Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss ICML 2024 DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data AISTATS 2024 Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization ICML 2024 Deep Fusion: Efficient Network Training via Pre-trained Initializations ICML 2024