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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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'25

Papers (including subtopics)

Learning to Encode Position for Transformer with Continuous Dynamical Model ICML 2020 Learning to Generate 3D Training Data Through Hybrid Gradient CVPR 2020 Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks EMNLP 2020 Learning to Learn by Zeroth-Order Oracle ICLR 2020 Learning to Link ICLR 2020 Learning to Mutate with Hypergradient Guided Population NeurIPS 2020 Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees AAAI 2020 Learning to Optimize Non-Rigid Tracking CVPR 2020 Learning to Optimize on SPD Manifolds CVPR 2020 Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees ICLR 2020 Learning to Play Sequential Games versus Unknown Opponents NeurIPS 2020 Learning to Rank Learning Curves ICML 2020 Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting AAAI 2020 Learning to Score Behaviors for Guided Policy Optimization ICML 2020 Learning to Select Base Classes for Few-Shot Classification CVPR 2020 Learning to Slide Unknown Objects with Differentiable Physics Simulations RSS 2020 Learning to solve the credit assignment problem ICLR 2020 Learning to solve TV regularised problems with unrolled algorithms NeurIPS 2020 Learning To Stop While Learning To Predict ICML 2020 Learning to Structure an Image With Few Colors CVPR 2020 Learning to Super Resolve Intensity Images From Events CVPR 2020 Learning transport cost from subset correspondence ICLR 2020 Learning under Model Misspecification: Applications to Variational and Ensemble methods NeurIPS 2020 Learning Weighted Model Integration Distributions AAAI 2020 Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders CVPR 2020