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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
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828
3,646
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2000
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Papers (including subtopics)

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models ICML 2021 PiRank: Scalable Learning To Rank via Differentiable Sorting NeurIPS 2021 Pixel-Perfect Structure-From-Motion With Featuremetric Refinement ICCV 2021 Planning from Pixels in Environments with Combinatorially Hard Search Spaces NeurIPS 2021 PLUGIn: A simple algorithm for inverting generative models with recovery guarantees NeurIPS 2021 PML: Progressive Margin Loss for Long-Tailed Age Classification CVPR 2021 PoA of Simple Auctions with Interdependent Values AAAI 2021 PODS: Policy Optimization via Differentiable Simulation ICML 2021 Point-Set Distances for Learning Representations of 3D Point Clouds ICCV 2021 Pointwise Bounds for Distribution Estimation under Communication Constraints NeurIPS 2021 Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks ICML 2021 Polarimetric Helmholtz Stereopsis ICCV 2021 Policy Analysis using Synthetic Controls in Continuous-Time ICML 2021 Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples ICLR 2021 Policy Gradient Bayesian Robust Optimization for Imitation Learning ICML 2021 Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning ICML 2021 Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses NeurIPS 2021 Polka Lines: Learning Structured Illumination and Reconstruction for Active Stereo CVPR 2021 Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning OSDI 2021 Polyjuice: High-Performance Transactions via Learned Concurrency Control OSDI 2021 Poly-NL: Linear Complexity Non-Local Layers With 3rd Order Polynomials ICCV 2021 Polynomial-Time in PDDL Input Size: Making the Delete Relaxation Feasible for Lifted Planning IJCAI 2021 Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization ICML 2021 Posterior Differential Regularization with f-divergence for Improving Model Robustness NAACL 2021 Posterior Meta-Replay for Continual Learning NeurIPS 2021