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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)

Identifying Selection Bias from Observational Data AAAI 2023 Identifying the limits of transformers when performing model-checking with natural language EACL 2023 Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space EACL 2023 IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse IJCAI 2023 ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation AAAI 2023 ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing CVPR 2023 Image Restoration with Mean-Reverting Stochastic Differential Equations ICML 2023 Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction ICLR 2023 ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced Recognition ICCV 2023 Imitation Learning from Imperfection: Theoretical Justifications and Algorithms NeurIPS 2023 IMP: Iterative Matching and Pose Estimation With Adaptive Pooling CVPR 2023 Implementing Contextual Biasing in GPU Decoder for Online ASR Interspeech 2023 Implications of Annotation Artifacts in Edge Probing Test Datasets CoNLL 2023 Implications of sparsity and high triangle density for graph representation learning AISTATS 2023 Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing COLT 2023 Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data ICLR 2023 Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability NeurIPS 2023 Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks JMLR 2023 Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data NeurIPS 2023 Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network NeurIPS 2023 Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming AAAI 2023 Implicit Graph Neural Networks: A Monotone Operator Viewpoint ICML 2023 Implicit Jacobian regularization weighted with impurity of probability output ICML 2023 Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving CVPR 2023 Implicit Regularization for Group Sparsity ICLR 2023