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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)

A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs NeurIPS 2021 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty ICML 2021 A Block Minifloat Representation for Training Deep Neural Networks ICLR 2021 A/B/n Testing with Control in the Presence of Subpopulations NeurIPS 2021 Absolute Neighbour Difference based Correlation Test for Detecting Heteroscedastic Relationships NeurIPS 2021 Abstraction-based branch and bound approach to Q-learning for hybrid optimal control L4DC 2021 A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer ALT 2021 ACAT-G: An Interactive Learning Framework for Assisted Response Generation AAAI 2021 Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm ICML 2021 Accelerated Combinatorial Search for Outlier Detection with Provable Bound on Sub-Optimality AAAI 2021 Accelerated Learning with Robustness to Adversarial Regressors L4DC 2021 Accelerated WGAN Update Strategy With Loss Change Rate Balancing WACV 2021 Accelerating Continuous Normalizing Flow with Trajectory Polynomial Regularization AAAI 2021 Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction ICLR 2021 Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning L4DC 2021 Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving ICML 2021 Accelerating Gossip SGD with Periodic Global Averaging ICML 2021 Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent JMLR 2021 Accelerating Metropolis-Hastings with Lightweight Inference Compilation AISTATS 2021 Accelerating Neural Architecture Search via Proxy Data IJCAI 2021 Accelerating Quadratic Optimization with Reinforcement Learning NeurIPS 2021 Acceleration via Fractal Learning Rate Schedules ICML 2021 Accessing Cloud with Disaggregated Software-Defined Router NSDI 2021 Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning NeurIPS 2021 Accounting for Confirmation Bias in Crowdsourced Label Aggregation IJCAI 2021