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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
352
828
3,646
5,854
2000
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Papers (including subtopics)

HyPe: Better Pre-trained Language Model Fine-tuning with Hidden Representation Perturbation ACL 2023 Hyperblock Floating Point: Generalised Quantization Scheme for Gradient and Inference Computation WACV 2023 Hyperbolic Chamfer Distance for Point Cloud Completion ICCV 2023 Hyperbolic VAE via Latent Gaussian Distributions NeurIPS 2023 HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork ICLR 2023 Hyperdimensional Feature Fusion for Out-of-Distribution Detection WACV 2023 HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning IJCAI 2023 Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks NeurIPS 2023 Hyperparameter Optimization through Neural Network Partitioning ICLR 2023 Hyperparameters in Reinforcement Learning and How To Tune Them ICML 2023 HyperPosePDF - Hypernetworks Predicting the Probability Distribution on SO(3) WACV 2023 HyperRouter: Towards Efficient Training and Inference of Sparse Mixture of Experts EMNLP 2023 Hyperspectral Image Denoising Using Uncertainty-Aware Adjustor IJCAI 2023 Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information ICML 2023 Hypervolume Maximization: A Geometric View of Pareto Set Learning NeurIPS 2023 HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork NeurIPS 2023 Hypothesis Selection with Memory Constraints NeurIPS 2023 Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability ICML 2023 I2C-Huelva at SemEval-2023 Task 10: Ensembling Transformers Models for the Detection of Online Sexism SemEval 2023 ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets NeurIPS 2023 Ideal Abstractions for Decision-Focused Learning AISTATS 2023 Identifiability and Generalizability in Constrained Inverse Reinforcement Learning ICML 2023 Identifiability Guarantees for Causal Disentanglement from Soft Interventions NeurIPS 2023 Identifiability of Label Noise Transition Matrix ICML 2023 Identification of Blackwell Optimal Policies for Deterministic MDPs AISTATS 2023