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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)

Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations AISTATS 2022 Probabilistic ODE Solutions in Millions of Dimensions ICML 2022 Probable Domain Generalization via Quantile Risk Minimization NeurIPS 2022 Probing as Quantifying Inductive Bias ACL 2022 Probing BERT’s priors with serial reproduction chains ACL 2022 Probing Script Knowledge from Pre-Trained Models EMNLP 2022 Probing Structured Pruning on Multilingual Pre-trained Models: Settings, Algorithms, and Efficiency ACL 2022 ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training ICML 2022 Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search WACV 2022 Project and Forget: Solving Large-Scale Metric Constrained Problems JMLR 2022 Projected Robust PCA with Application to Smooth Image Recovery JMLR 2022 Projection-free Distributed Online Learning with Sublinear Communication Complexity JMLR 2022 Projection Predictive Inference for Generalized Linear and Additive Multilevel Models AISTATS 2022 Projective Manifold Gradient Layer for Deep Rotation Regression CVPR 2022 projUNN: efficient method for training deep networks with unitary matrices NeurIPS 2022 Proof of Learning: Towards a Practical Blockchain Consensus Mechanism Using Directed Guiding Gradients (Student Abstract) AAAI 2022 Proppo: a Message Passing Framework for Customizable and Composable Learning Algorithms NeurIPS 2022 Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients ICLR 2022 ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model NeurIPS 2022 Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out ICML 2022 Provable Adversarial Robustness for Fractional Lp Threat Models AISTATS 2022 Provable Domain Generalization via Invariant-Feature Subspace Recovery ICML 2022 Provable General Function Class Representation Learning in Multitask Bandits and MDP NeurIPS 2022 Provable Generalization of Overparameterized Meta-learning Trained with SGD NeurIPS 2022 Provable Guarantees for Understanding Out-of-Distribution Detection AAAI 2022