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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)

An online passive-aggressive algorithm for difference-of-squares classification NeurIPS 2021 An online semi-definite programming with a generalised log-determinant regularizer and its applications ACML 2021 An Online Sequential Test for Qualitative Treatment Effects JMLR 2021 A Nonmyopic Approach to Cost-Constrained Bayesian Optimization UAI 2021 A nonparametric method for gradual change problems with statistical guarantees NeurIPS 2021 An Optimistic Acceleration of AMSGrad for Nonconvex Optimization ACML 2021 An optimization and generalization analysis for max-pooling networks UAI 2021 A Normative and Biologically Plausible Algorithm for Independent Component Analysis NeurIPS 2021 A Novel Estimator of Mutual Information for Learning to Disentangle Textual Representations ACL 2021 A Novel Method to Solve Neural Knapsack Problems ICML 2021 A novel notion of barycenter for probability distributions based on optimal weak mass transport NeurIPS 2021 A Novel Sequential Coreset Method for Gradient Descent Algorithms ICML 2021 An Overview of Uncertainty Calibration for Text Classification and the Role of Distillation ACL 2021 Answering Complex Causal Queries With the Maximum Causal Set Effect NeurIPS 2021 Antipodes of Label Differential Privacy: PATE and ALIBI NeurIPS 2021 A Nullspace Property for Subspace-Preserving Recovery ICML 2021 A One-Size-Fits-All Solution to Conservative Bandit Problems AAAI 2021 A PAC-Bayes Analysis of Adversarial Robustness NeurIPS 2021 A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks ICLR 2021 A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits AISTATS 2021 A Permutation-Equivariant Neural Network Architecture For Auction Design AAAI 2021 A Polynomial-time, Truthful, Individually Rational and Budget Balanced Ridesharing Mechanism IJCAI 2021 Application of kernel hypothesis testing on set-valued data UAI 2021 Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories MLHC 2021 Approximate Data Deletion from Machine Learning Models AISTATS 2021