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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)

Training Debiased Subnetworks With Contrastive Weight Pruning CVPR 2023 Training Deep Surrogate Models with Large Scale Online Learning ICML 2023 Training Energy-Based Normalizing Flow with Score-Matching Objectives NeurIPS 2023 Training-Free Neural Active Learning with Initialization-Robustness Guarantees ICML 2023 Training-free Neural Architecture Search for RNNs and Transformers ACL 2023 Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete NeurIPS 2023 Training Meta-Surrogate Model for Transferable Adversarial Attack AAAI 2023 Training Neural Networks is NP-Hard in Fixed Dimension NeurIPS 2023 Training neural operators to preserve invariant measures of chaotic attractors NeurIPS 2023 Training Normalizing Flows from Dependent Data ICML 2023 Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? NeurIPS 2023 Training-Time Attacks against K-nearest Neighbors AAAI 2023 Training Trajectories of Language Models Across Scales ACL 2023 Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory NeurIPS 2023 Trajectory Unified Transformer for Pedestrian Trajectory Prediction ICCV 2023 TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models ICCV 2023 TRAK: Attributing Model Behavior at Scale ICML 2023 Transcending Scaling Laws with 0.1% Extra Compute EMNLP 2023 Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings NeurIPS 2023 Transfer Knowledge From Head to Tail: Uncertainty Calibration Under Long-Tailed Distribution CVPR 2023 Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations AAAI 2023 Transformed Distribution Matching for Missing Value Imputation ICML 2023 Transformed Gaussian Processes for Characterizing a Model’s Discrepancy ACML 2023 Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks NeurIPS 2023 Transformer-based Hebrew NLP models for Short Answer Scoring in Biology ACL 2023