Cover Image

A Generalized Mean Approach for Distributed-PCA

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jou, Zhi-Yu, Huang, Su-Yun, Hung, Hung, Eguchi, Shinto
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The $ϕ$-PCA Framework: A Unified and Efficiency-Preserving Approach with Robust Variants
by: Hung, Hung, et al.
Published: (2025)

Statistical Inference via Generative Models: Flow Matching and Causal Inference
by: Eguchi, Shinto
Published: (2026)

Implicit geometric regularization in flow matching via density weighted Stein operators
by: Eguchi, Shinto
Published: (2025)

Robust inference using density-powered Stein operators
by: Eguchi, Shinto
Published: (2025)

Generative and Nonparametric Approaches for Conditional Distribution Estimation: Methods, Perspectives, and Comparative Evaluations
by: Chin, Yen-Shiu, et al.
Published: (2026)

Information Geometry for Maximum Diversity Distributions
by: Eguchi, Shinto
Published: (2024)

On the efficiency-loss free ordering-robustness of product-PCA
by: Hung, Hung, et al.
Published: (2023)

GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection
by: Seleznova, Mariia, et al.
Published: (2025)

Mean-Shift PCA by Knockoff Mean
by: Li, Mengda, et al.
Published: (2026)

Minimum Gamma Divergence for Regression and Classification Problems
by: Eguchi, Shinto
Published: (2024)

Kernel PCA for Out-of-Distribution Detection
by: Fang, Kun, et al.
Published: (2024)

On the asymptotic properties of product-PCA under the high-dimensional setting
by: Hung, Hung, et al.
Published: (2024)

Learning in the Fisher Subspace: A Guided Initialization for LoRA Fine-Tuning
by: Feng, Zhi-Quan, et al.
Published: (2026)

An AI-powered Bayesian Generative Modeling Approach for Arbitrary Conditional Inference
by: Liu, Qiao, et al.
Published: (2026)

Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models
by: Nguyen, Manh, et al.
Published: (2025)

Multi-Dimensional Model Integrity and Responsibility Assessment Index and Scoring Framework
by: Nguyen, Phuc Truong Loc, et al.
Published: (2026)

Thinking Deeper, Not Longer: Depth-Recurrent Transformers for Compositional Generalization
by: Chen, Hung-Hsuan
Published: (2026)

Retrieval-augmented Decoding for Improving Truthfulness in Open-ended Generation
by: Nguyen, Manh, et al.
Published: (2025)

Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching
by: Lu, Wenhui Sophia, et al.
Published: (2025)

Flexible Bivariate Beta Mixture Model: A Probabilistic Approach for Clustering Complex Data Structures
by: Hsu, Yung-Peng, et al.
Published: (2025)

On a class of binary regression models and their robust estimation
by: Hayashi, Kenichi, et al.
Published: (2025)

Minimum Copula Divergence for Robust Estimation
by: Eguchi, Shinto, et al.
Published: (2025)

Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learning
by: Gau, Rung-Hung, et al.
Published: (2024)

XEdgeAI: A Human-centered Industrial Inspection Framework with Data-centric Explainable Edge AI Approach
by: Nguyen, Truong Thanh Hung, et al.
Published: (2024)

High-Dimensional Asymptotics of Differentially Private PCA
by: Yun, Youngjoo, et al.
Published: (2025)

LJ-Bench: Ontology-Based Benchmark for U.S. Crime
by: Tseng, Hung Yun, et al.
Published: (2026)

Enhancing Offline Model-Based RL via Active Model Selection: A Bayesian Optimization Perspective
by: Yang, Yu-Wei, et al.
Published: (2025)

Graph Regularized PCA
by: Briola, Antonio, et al.
Published: (2026)

Continual Fine-Tuning of Large Language Models via Program Memory
by: Le, Hung, et al.
Published: (2026)

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization
by: Nguyen, Hy, et al.
Published: (2025)

Understanding Gradient Boosting Classifier: Training, Prediction, and the Role of $γ_j$
by: Chen, Hung-Hsuan
Published: (2024)

Uncertainty-Aware PCA for Arbitrarily Distributed Data Modeled by Gaussian Mixture Models
by: Klötzl, Daniel, et al.
Published: (2025)

A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems
by: Tran, Hung Vinh, et al.
Published: (2024)

Low-Precision Streaming PCA
by: Dasgupta, Sanjoy, et al.
Published: (2025)

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selections and Approximations
by: Fang, Kun, et al.
Published: (2025)

Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework Approach
by: Lin, ChungYi, et al.
Published: (2024)

A PCA-based Data Prediction Method
by: Daugulis, Peteris, et al.
Published: (2025)

Trend Extrapolation for Technology Forecasting: Leveraging LSTM Neural Networks for Trend Analysis of Space Exploration Vessels
by: Tsai, Peng-Hung, et al.
Published: (2025)

A Geometric Analysis of PCA
by: Hanchi, Ayoub El, et al.
Published: (2025)

Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee
by: Hung, Yu-Heng, et al.
Published: (2025)