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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)

Reinforcement Learning for Adaptive Mesh Refinement AISTATS 2023 Reinforcement Learning for Branch-and-Bound Optimisation Using Retrospective Trajectories AAAI 2023 Reinforcement Learning for Joint Optimization of Multiple Rewards JMLR 2023 Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space ICML 2023 Reinforcement Learning with Simple Sequence Priors NeurIPS 2023 Reject Decoding via Language-Vision Models for Text-to-Image Synthesis AAAI 2023 Relational Debugging --- Pinpointing Root Causes of Performance Problems OSDI 2023 Relation-aware Ensemble Learning for Knowledge Graph Embedding EMNLP 2023 Relative Entropic Optimal Transport: a (Prior-aware) Matching Perspective to (Unbalanced) Classification NeurIPS 2023 Reliable Gradient-free and Likelihood-free Prompt Tuning EACL 2023 Reliable learning in challenging environments NeurIPS 2023 ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation NeurIPS 2023 Remixing-based Unsupervised Source Separation from Scratch Interspeech 2023 Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD JMLR 2023 REPAIR: REnormalizing Permuted Activations for Interpolation Repair ICLR 2023 Reparameterization through Spatial Gradient Scaling ICLR 2023 Re-parameterizing Your Optimizers rather than Architectures ICLR 2023 Repeated Bilateral Trade Against a Smoothed Adversary COLT 2023 Rephrasing the Reference for Non-autoregressive Machine Translation AAAI 2023 Replicability in Reinforcement Learning NeurIPS 2023 Replicable Bandits ICLR 2023 Replicable Clustering NeurIPS 2023 Replicable Reinforcement Learning NeurIPS 2023 Replicating Persistent Memory Key-Value Stores with Efficient RDMA Abstraction OSDI 2023 Representational Dissimilarity Metric Spaces for Stochastic Neural Networks ICLR 2023