Copertina

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Tian, Ye, Weng, Haolei, Xia, Lucy, Feng, Yang
Natura:	Preprint
Pubblicazione:	2022
Soggetti:	Machine Learning Statistics Theory Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Federated Transfer Learning with Differential Privacy
di: Li, Mengchu, et al.
Pubblicazione: (2024)

Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
di: Thai, Tuan, et al.
Pubblicazione: (2025)

Knowledge-Embedded Latent Projection for Robust Representation Learning
di: Tang, Weijing, et al.
Pubblicazione: (2026)

Estimating the Number of Components in Finite Mixture Models via Variational Approximation
di: Wang, Chenyang, et al.
Pubblicazione: (2024)

Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning
di: Shen, Ye, et al.
Pubblicazione: (2021)

Dendrograms of Mixing Measures for Softmax-Gated Gaussian Mixture of Experts: Consistency without Model Sweeps
di: Hai, Do Tien, et al.
Pubblicazione: (2025)

Transfer Learning for High-dimensional Quantile Regression with Distribution Shift
di: Bai, Ruiqi, et al.
Pubblicazione: (2024)

Transfer Learning for Causal Effect Estimation
di: Wei, Song, et al.
Pubblicazione: (2023)

Transfer Learning for Classification under Decision Rule Drift with Application to Optimal Individualized Treatment Rule Estimation
di: Wang, Xiaohan, et al.
Pubblicazione: (2025)

Transfer Learning for Nonparametric Contextual Dynamic Pricing
di: Wang, Fan, et al.
Pubblicazione: (2025)

Functional Linear Non-Gaussian Acyclic Model for Causal Discovery
di: Yang, Tian-Le, et al.
Pubblicazione: (2024)

Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning
di: Guo, Zijian, et al.
Pubblicazione: (2022)

Bayesian Semiparametric Mixture Cure (Frailty) Models
di: Kızılaslan, Fatih, et al.
Pubblicazione: (2025)

Adaptive Confidence Intervals in Efron's Gaussian Two-Groups Model
di: Wang, Qiaosen, et al.
Pubblicazione: (2026)

Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
di: Ge, Jiawei, et al.
Pubblicazione: (2024)

Transfer Learning with Distance Covariance for Random Forest: Error Bounds and an EHR Application
di: Li, Chenze, et al.
Pubblicazione: (2025)

A Tutorial on Doubly Robust Learning for Causal Inference
di: Hlynsson, Hlynur Davíð
Pubblicazione: (2024)

Le Cam Distortion: A Decision-Theoretic Framework for Robust Transfer Learning
di: Akdemir, Deniz
Pubblicazione: (2025)

Structural Foundations for Leading Digit Laws: Beyond Probabilistic Mixtures
di: Berman, Vladimir
Pubblicazione: (2025)

On Multiple Robustness of Proximal Dynamic Treatment Regimes
di: Gao, Yuanshan, et al.
Pubblicazione: (2025)

AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regression
di: He, Zelin, et al.
Pubblicazione: (2024)

Minimax-Optimal Spectral Clustering with Covariance Projection for High-Dimensional Anisotropic Mixtures
di: Huang, Chengzhu, et al.
Pubblicazione: (2025)

Fast Model Selection and Stable Optimization for Softmax-Gated Multinomial-Logistic Mixture of Experts Models
di: Tran, TrungKhang, et al.
Pubblicazione: (2026)

Discrete Gaussian Vector Fields On Meshes
di: Gillan, Michael, et al.
Pubblicazione: (2025)

Multi-environment Invariance Learning with Missing Data
di: Jia, Yiran, et al.
Pubblicazione: (2026)

Rolled Gaussian process models for curves on manifolds
di: Preston, Simon, et al.
Pubblicazione: (2025)

Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
di: de Surrel, Thibault, et al.
Pubblicazione: (2025)

Adaptive finite element type decomposition of Gaussian processes
di: Kim, Jaehoan, et al.
Pubblicazione: (2025)

Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective
di: Takada, Masaaki, et al.
Pubblicazione: (2023)

The Decaying Missing-at-Random Framework: Model Doubly Robust Causal Inference with Partially Labeled Data
di: Zhang, Yuqian, et al.
Pubblicazione: (2023)

Generalized Data Thinning Using Sufficient Statistics
di: Dharamshi, Ameer, et al.
Pubblicazione: (2023)

Learning Robust Treatment Rules for Censored Data
di: Cui, Yifan, et al.
Pubblicazione: (2024)

Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget
di: Kato, Masahiro
Pubblicazione: (2023)

Large-Sample Properties of Non-Stationary Source Separation for Gaussian Signals
di: Bachoc, François, et al.
Pubblicazione: (2022)

Anytime-valid t-tests and confidence sequences for Gaussian means with unknown variance
di: Wang, Hongjian, et al.
Pubblicazione: (2023)

Powerful rank verification for multivariate Gaussian data with any covariance structure
di: Sood, Anav
Pubblicazione: (2025)

On the Robustness of Kernel Goodness-of-Fit Tests
di: Liu, Xing, et al.
Pubblicazione: (2024)

Robust Point Matching with Distance Profiles
di: Hur, YoonHaeng, et al.
Pubblicazione: (2023)

ARK: Robust Knockoffs Inference with Coupling
di: Fan, Yingying, et al.
Pubblicazione: (2023)

Fast and Provably Accurate Sequential Designs using Hilbert Space Gaussian Processes
di: Zhu, Huanyan, et al.
Pubblicazione: (2026)