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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)

Long-Tailed Learning Requires Feature Learning ICLR 2023 Long-Tailed Visual Recognition via Self-Heterogeneous Integration With Knowledge Excavation CVPR 2023 Long-Term Fairness with Unknown Dynamics NeurIPS 2023 Lookahead When It Matters: Adaptive Non-causal Transformers for Streaming Neural Transducers ICML 2023 Lookaround Optimizer: k steps around, 1 step average NeurIPS 2023 Look-back Decoding for Open-Ended Text Generation EMNLP 2023 Loosely consistent emphatic temporal-difference learning UAI 2023 Loss Balancing for Fair Supervised Learning ICML 2023 Loss-Curvature Matching for Dataset Selection and Condensation AISTATS 2023 Loss Dynamics of Temporal Difference Reinforcement Learning NeurIPS 2023 Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent ICLR 2023 Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost AAAI 2023 Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability ICML 2023 Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set ICML 2023 Lower Bounds and Accelerated Algorithms for Bilevel Optimization JMLR 2023 Lower Bounds for Learning in Revealing POMDPs ICML 2023 Lower Bounds for the Convergence of Tensor Power Iteration on Random Overcomplete Models COLT 2023 Lower Bounds on Adaptive Sensing for Matrix Recovery NeurIPS 2023 Lowering the Pre-training Tax for Gradient-based Subset Training: A Lightweight Distributed Pre-Training Toolkit ICML 2023 Low-Light Image Enhancement Network Based on Multi-Scale Feature Complementation AAAI 2023 Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence JMLR 2023 Low-resource grapheme-to-phoneme mapping with phonetically-conditioned transfer ACL 2023 Low Tensor Rank Learning of Neural Dynamics NeurIPS 2023 Low Tree-Rank Bayesian Vector Autoregression Models JMLR 2023 Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single ICML 2023