Image de couverture de livre

Multi-Task Learning with Summary Statistics

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Knight, Parker, Duan, Rui
Format:	Preprint
Publié:	2023
Sujets:	Methodology Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Multi-Task Learning for Sparsity Pattern Heterogeneity: Statistical and Computational Perspectives
par: Behdin, Kayhan, et autres
Publié: (2022)

Latent Factor Point Processes for Patient Representation in Electronic Health Records
par: Knight, Parker, et autres
Publié: (2025)

Unifying Summary Statistic Selection for Approximate Bayesian Computation
par: Hoffmann, Till, et autres
Publié: (2022)

Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs
par: Chakraborty, Atlanta, et autres
Publié: (2025)

SMART: A Spectral Transfer Approach to Multi-Task Learning
par: Zhao, Boxin, et autres
Publié: (2026)

Statistical Theory of Multi-stage Newton Iteration Algorithm for Online Continual Learning
par: Lu, Xinjia, et autres
Publié: (2025)

Robust and Adaptive Spectral Method for Representation Multi-Task Learning with Contamination
par: Huang, Yian, et autres
Publié: (2025)

Statistical Inference for Matching Decisions via Matrix Completion under Dependent Missingness
par: Duan, Congyuan, et autres
Publié: (2025)

Robust Learning of Heterogeneous Dynamic Systems
par: Xu, Shuoxun, et autres
Publié: (2026)

GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds
par: Chen, Aoran, et autres
Publié: (2025)

Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit
par: Zhang, Chaozhi, et autres
Publié: (2024)

Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings
par: Sui, Yang, et autres
Publié: (2025)

Multi-Study R-Learner for Estimating Heterogeneous Treatment Effects Across Studies Using Statistical Machine Learning
par: Shyr, Cathy, et autres
Publié: (2023)

Self-Supervised Learning with Gaussian Processes
par: Duan, Yunshan, et autres
Publié: (2025)

Learning Centre Partitions from Summaries
par: Debaly, Zinsou Max, et autres
Publié: (2025)

Statistical Learning for Heterogeneous Treatment Effects: Pretraining, Prognosis, and Prediction
par: Schuessler, Maximilian, et autres
Publié: (2025)

Task-Agnostic Machine-Learning-Assisted Inference
par: Miao, Jiacheng, et autres
Publié: (2024)

Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Decoding
par: Xu, Shuoxun, et autres
Publié: (2026)

A Unified Hierarchical Multi-Task Multi-Fidelity Framework for Data-Efficient Surrogate Modeling in Manufacturing
par: Mehta, Manan, et autres
Publié: (2026)

Sparklen: A Statistical Learning Toolkit for High-Dimensional Hawkes Processes in Python
par: Lacoste, Romain Edmond
Publié: (2025)

LEARNER: A Transfer Learning Method for Low-Rank Matrix Estimation
par: McGrath, Sean, et autres
Publié: (2024)

Task-tailored Pre-processing: Fair Downstream Supervised Learning
par: Sohn, Jinwon, et autres
Publié: (2026)

Active Statistical Inference
par: Zrnic, Tijana, et autres
Publié: (2024)

Connecting Algorithmic Fairness to Quality Dimensions in Machine Learning in Official Statistics and Survey Production
par: Schenk, Patrick Oliver, et autres
Publié: (2024)

Statistically Efficient Bayesian Sequential Experiment Design via Reinforcement Learning with Cross-Entropy Estimators
par: Blau, Tom, et autres
Publié: (2023)

Fast and robust invariant generalized linear models
par: Knight, Parker, et autres
Publié: (2025)

Statistical ranking with dynamic covariates
par: Dong, Pinjun, et autres
Publié: (2024)

Statistical Inference for Fuzzy Clustering
par: Wu, Qiuyi, et autres
Publié: (2026)

Conformal Calibration of Statistical Confidence Sets
par: Cabezas, Luben M. C., et autres
Publié: (2024)

Adaptive Multi-task Learning for Multi-sector Portfolio Optimization
par: Fan, Qingliang, et autres
Publié: (2025)

Extrapolation in Statistical Learning with Extreme Value Theory
par: Engelke, Sebastian, et autres
Publié: (2026)

LIDS: LLM Summary Inference Under the Layered Lens
par: Park, Dylan, et autres
Publié: (2026)

Statistical Inference for Differentially Private Stochastic Gradient Descent
par: Xia, Xintao, et autres
Publié: (2025)

$ϕ$-Table: A Statistical Explanation for Global SHAP
par: Kim, Dongseok, et autres
Publié: (2025)

Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
par: Imai, Kosuke, et autres
Publié: (2022)

Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information
par: Ma, Shujie, et autres
Publié: (2024)

False Discovery Rate Control via Bayesian Mirror Statistic
par: Molinari, Marco, et autres
Publié: (2025)

Wahkon: A Statistically Principled Deep RKHS Superposition Network
par: Chen, Yongkai, et autres
Publié: (2026)

Statistical Inference Leveraging Synthetic Data with Distribution-Free Guarantees
par: Bashari, Meshi, et autres
Publié: (2025)

Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference
par: Arruda, Jonas, et autres
Publié: (2026)