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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)

Fast Graph Neural Tangent Kernel via Kronecker Sketching AAAI 2022 Fast Instrument Learning with Faster Rates NeurIPS 2022 Fast Lossless Neural Compression with Integer-Only Discrete Flows ICML 2022 Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay NeurIPS 2022 Fast Monte-Carlo Approximation of the Attention Mechanism AAAI 2022 Fast Neural Kernel Embeddings for General Activations NeurIPS 2022 Fast Population-Based Reinforcement Learning on a Single Machine ICML 2022 Fast predictive uncertainty for classification with Bayesian deep networks UAI 2022 Fast Provably Robust Decision Trees and Boosting ICML 2022 Fast Rank-1 NMF for Missing Data with KL Divergence AISTATS 2022 Fast-Rate PAC-Bayesian Generalization Bounds for Meta-Learning ICML 2022 Fast rates for noisy interpolation require rethinking the effect of inductive bias ICML 2022 Fast Regression for Structured Inputs ICLR 2022 Fast Sparse Classification for Generalized Linear and Additive Models AISTATS 2022 Fast Sparse Decision Tree Optimization via Reference Ensembles AAAI 2022 Fast topological clustering with Wasserstein distance ICLR 2022 Feature and Instance Joint Selection: A Reinforcement Learning Perspective IJCAI 2022 Feature and Parameter Selection in Stochastic Linear Bandits ICML 2022 Feature Collapsing for Gaussian Process Variable Ranking AISTATS 2022 Feature Generation and Hypothesis Verification for Reliable Face Anti-spoofing AAAI 2022 Feature Importance Explanations for Temporal Black-Box Models AAAI 2022 Feature learning and random features in standard finite-width convolutional neural networks: An empirical study UAI 2022 Feature Learning and Signal Propagation in Deep Neural Networks ICML 2022 Feature Learning in L_2-regularized DNNs: Attraction/Repulsion and Sparsity NeurIPS 2022 Feature screening with kernel knockoffs AISTATS 2022