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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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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning AAAI 2021 Cardinality constrained submodular maximization for random streams NeurIPS 2021 Cardinality-Regularized Hawkes-Granger Model NeurIPS 2021 CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator NeurIPS 2021 Cascaded Head-colliding Attention ACL 2021 Cascade Network with Guided Loss and Hybrid Attention for Finding Good Correspondences AAAI 2021 Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference? ACL 2021 Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication NeurIPS 2021 Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization ICML 2021 CATE: Computation-aware Neural Architecture Encoding with Transformers ICML 2021 Catformer: Designing Stable Transformers via Sensitivity Analysis ICML 2021 Causal Bandits with Unknown Graph Structure NeurIPS 2021 Causal Effect Inference for Structured Treatments NeurIPS 2021 Causal Inference with Selectively Deconfounded Data AISTATS 2021 Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners ICML 2021 Causal Modeling with Stochastic Confounders AISTATS 2021 Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation COLT 2021 CBP: backpropagation with constraint on weight precision using a pseudo-Lagrange multiplier method NeurIPS 2021 Center Smoothing: Certified Robustness for Networks with Structured Outputs NeurIPS 2021 CentripetalText: An Efficient Text Instance Representation for Scene Text Detection NeurIPS 2021 Certification of iterative predictions in Bayesian neural networks UAI 2021 Certified Robustness to Programmable Transformations in LSTMs EMNLP 2021 Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization L4DC 2021 CFR-MIX: Solving Imperfect Information Extensive-Form Games with Combinatorial Action Space IJCAI 2021 ChaCha for Online AutoML ICML 2021