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

Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive? ICLR 2023 Deep learning with kernels through RKHM and the Perron-Frobenius operator NeurIPS 2023 Deep linear networks can benignly overfit when shallow ones do JMLR 2023 Deeply Supervised Curriculum Learning for Deep Neural Network-based Sound Source Localization Interspeech 2023 DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network CVPR 2023 Deep Momentum Multi-Marginal Schrödinger Bridge NeurIPS 2023 DeePMOS: Deep Posterior Mean-Opinion-Score of Speech Interspeech 2023 Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model NeurIPS 2023 Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility JMLR 2023 Deep Off-Policy Iterative Learning Control L4DC 2023 DeepPCR: Parallelizing Sequential Operations in Neural Networks NeurIPS 2023 Deep Perturbation Learning: Enhancing the Network Performance via Image Perturbations ICML 2023 Deep Random Projector: Accelerated Deep Image Prior CVPR 2023 Deep Ranking Ensembles for Hyperparameter Optimization ICLR 2023 Deep Recurrent Optimal Stopping NeurIPS 2023 Deep Reinforcement Learning with Plasticity Injection NeurIPS 2023 Deep Stochastic Processes via Functional Markov Transition Operators NeurIPS 2023 Deep Temporal Sets with Evidential Reinforced Attentions for Unique Behavioral Pattern Discovery ICML 2023 Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation ICLR 2023 Deep Value Function Networks for Large-Scale Multistage Stochastic Programs AISTATS 2023 Deep Variational Implicit Processes ICLR 2023 Defects of Convolutional Decoder Networks in Frequency Representation ICML 2023 DEFT: Dexterous Fine-Tuning for Hand Policies CoRL 2023 Degradation-Resistant Unfolding Network for Heterogeneous Image Fusion ICCV 2023 Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback ICML 2023