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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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828
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Papers (including subtopics)

Training Your Sparse Neural Network Better with Any Mask ICML 2022 Trajectories predicted by optimal speech motor control using LSTM networks Interspeech 2022 Trajectory Inference via Mean-field Langevin in Path Space NeurIPS 2022 Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions NeurIPS 2022 Trajectory Optimization for Physics-Based Reconstruction of 3D Human Pose From Monocular Video CVPR 2022 Transductive Robust Learning Guarantees AISTATS 2022 Transferable Adversarial Attack based on Integrated Gradients ICLR 2022 Transfer Learning in Information Criteria-based Feature Selection JMLR 2022 Transferring Knowledge via Neighborhood-Aware Optimal Transport for Low-Resource Hate Speech Detection AACL 2022 Transformer-based quality assessment model for generalized user-generated multimedia audio content Interspeech 2022 Transformer-based Transform Coding ICLR 2022 Transformer Language Models without Positional Encodings Still Learn Positional Information EMNLP 2022 Transformer Networks for Non-Intrusive Speech Quality Prediction Interspeech 2022 Transformer Quality in Linear Time ICML 2022 Transformers Can Do Bayesian Inference ICLR 2022 Transformers from an Optimization Perspective NeurIPS 2022 Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost NeurIPS 2022 Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture NeurIPS 2022 Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models ICLR 2022 Transkimmer: Transformer Learns to Layer-wise Skim ACL 2022 Transmission-Guided Bayesian Generative Model for Smoke Segmentation AAAI 2022 Tree-based Node Aggregation in Sparse Graphical Models JMLR 2022 Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks NeurIPS 2022 Tree-Values: Selective Inference for Regression Trees JMLR 2022 TRGP: Trust Region Gradient Projection for Continual Learning ICLR 2022