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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
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2000
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Papers (including subtopics)

Variational Inference MPC using Tsallis Divergence RSS 2021 Variational inference with continuously-indexed normalizing flows UAI 2021 Variational Information Bottleneck for Effective Low-Resource Audio Classification Interspeech 2021 Variational Model-based Policy Optimization IJCAI 2021 Variational refinement for importance sampling using the forward Kullback-Leibler divergence UAI 2021 VarifocalNet: An IoU-Aware Dense Object Detector CVPR 2021 Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms ICLR 2021 Vector Quantized Bayesian Neural Network Inference for Data Streams AAAI 2021 Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds ACML 2021 Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels NeurIPS 2021 Verifying Reinforcement Learning up to Infinity IJCAI 2021 Versatile Verification of Tree Ensembles ICML 2021 View Generalization for Single Image Textured 3D Models CVPR 2021 ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search CVPR 2021 Vis2Mesh: Efficient Mesh Reconstruction From Unstructured Point Clouds of Large Scenes With Learned Virtual View Visibility ICCV 2021 Visualizing the Emergence of Intermediate Visual Patterns in DNNs NeurIPS 2021 von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning ICCV 2021 VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization NeurIPS 2021 vqSGD: Vector Quantized Stochastic Gradient Descent AISTATS 2021 VSQL: Variational Shadow Quantum Learning for Classification AAAI 2021 V-statistics and Variance Estimation JMLR 2021 Warm Starting CMA-ES for Hyperparameter Optimization AAAI 2021 Wasserstein-2 Generative Networks ICLR 2021 Wasserstein Barycenter for Multi-Source Domain Adaptation CVPR 2021 Wasserstein barycenters can be computed in polynomial time in fixed dimension JMLR 2021