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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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Papers (including subtopics)

Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set UAI 2022 Pareto Optimal Model Selection in Linear Bandits AISTATS 2022 Pareto Set Learning for Expensive Multi-Objective Optimization NeurIPS 2022 Parsimonious Learning-Augmented Caching ICML 2022 Partial Class Activation Attention for Semantic Segmentation CVPR 2022 Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task EMNLP 2022 Partial likelihood Thompson sampling UAI 2022 Partially adaptive regularized multiple regression analysis for estimating linear causal effects UAI 2022 Partially Does It: Towards Scene-Level FG-SBIR With Partial Input CVPR 2022 Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving CoRL 2022 Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization ICLR 2022 Partitioned Gradient Matching-based Data Subset Selection for Compute-Efficient Robust ASR Training EMNLP 2022 Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models EMNLP 2022 Patch Slimming for Efficient Vision Transformers CVPR 2022 PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks AAAI 2022 PathFlow: A normalizing flow generator that finds transition paths UAI 2022 Path-Gradient Estimators for Continuous Normalizing Flows ICML 2022 Path Independent Equilibrium Models Can Better Exploit Test-Time Computation NeurIPS 2022 Path Integral Sampler: A Stochastic Control Approach For Sampling ICLR 2022 PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models EMNLP 2022 Pay attention to your loss : understanding misconceptions about Lipschitz neural networks NeurIPS 2022 PCEE-BERT: Accelerating BERT Inference via Patient and Confident Early Exiting NAACL 2022 PDE-Based Optimal Strategy for Unconstrained Online Learning ICML 2022 PDEBench: An Extensive Benchmark for Scientific Machine Learning NeurIPS 2022 PDQ-Net: Deep probabilistic dual quaternion network for absolute pose regression on $SE(3)$ UAI 2022