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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)

Training Networks in Null Space of Feature Covariance for Continual Learning CVPR 2021 Training Neural Networks is ER-complete NeurIPS 2021 Training Neural Networks with Fixed Sparse Masks NeurIPS 2021 Training Over-parameterized Models with Non-decomposable Objectives NeurIPS 2021 Training Quantized Neural Networks to Global Optimality via Semidefinite Programming ICML 2021 Training Recurrent Neural Networks via Forward Propagation Through Time ICML 2021 Training Spiking Neural Networks with Accumulated Spiking Flow AAAI 2021 Training with Quantization Noise for Extreme Model Compression ICLR 2021 Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021 Transferable Semantic Augmentation for Domain Adaptation CVPR 2021 Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization NeurIPS 2021 Transfer Learning via Optimal Transportation for Integrative Cancer Patient Stratification IJCAI 2021 Transformer Interpretability Beyond Attention Visualization CVPR 2021 TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search CVPR 2021 Treatment Effect Estimation with Disentangled Latent Factors AAAI 2021 Trembling-Hand Perfection and Correlation in Sequential Games AAAI 2021 Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction ACL 2021 TrivialAugment: Tuning-Free Yet State-of-the-Art Data Augmentation ICCV 2021 Truncated Marginal Neural Ratio Estimation NeurIPS 2021 Trusted-maximizers entropy search for efficient Bayesian optimization UAI 2021 Trusted Multi-View Classification ICLR 2021 Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes CoRL 2021 Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits JMLR 2021 T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP ICML 2021 TUDA-CCL at SemEval-2021 Task 1: Using Gradient-boosted Regression Tree Ensembles Trained on a Heterogeneous Feature Set for Predicting Lexical Complexity SemEval 2021