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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)

f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences NeurIPS 2023 Fractal Landscapes in Policy Optimization NeurIPS 2023 Francis Bacon at SemEval-2023 Task 4: Ensembling BERT and GloVe for Value Identification in Arguments SemEval 2023 FRA-RIR: Fast Random Approximation of the Image-source Method Interspeech 2023 Free Energy of Bayesian Convolutional Neural Network with Skip Connection ACML 2023 Free-Form Variational Inference for Gaussian Process State-Space Models ICML 2023 Free Lunch for Efficient Textual Commonsense Integration in Language Models ACL 2023 FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning ICLR 2023 FreeREA: Training-Free Evolution-Based Architecture Search WACV 2023 Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise AISTATS 2023 Frequency-Aware Self-Supervised Monocular Depth Estimation WACV 2023 Frequency Domain-Based Dataset Distillation NeurIPS 2023 Frequency Domain Gaussian Process Models for $H^∞$ Uncertainties L4DC 2023 From t-SNE to UMAP with contrastive learning ICLR 2023 From Adaptive Query Release to Machine Unlearning ICML 2023 From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection ICCV 2023 From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions JMLR 2023 From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks COLT 2023 From Hypergraph Energy Functions to Hypergraph Neural Networks ICML 2023 From Interval to Ordinal: A HMM based Approach for Emotion Label Conversion Interspeech 2023 From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning ICML 2023 From Pseudorandomness to Multi-Group Fairness and Back COLT 2023 From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks ICML 2023 From Robustness to Privacy and Back ICML 2023 From Shapley Values to Generalized Additive Models and back AISTATS 2023