paper-with-me

Papers

Learning Label Initialization for Time-Dependent Harmonic Extension

2022-05-03 · Amitoz Azad

Node classification on graphs can be formulated as the Dirichlet problem on graphs where the signal is given at the labeled nodes, and the harmonic extension is done on the unlabeled nodes. This paper considers a time-dependent version of the Dirichlet problem on graphs and shows how to improve its solution by learning the proper initialization vector on the unlabeled nodes. Further, we show that the improved solution is at par with state-of-the-art methods used for node classification. Finally, we conclude this paper by discussing the importance of parameter t, pros, and future directions.

📄 PDF Abstract BibTeX arXiv:2205.01358

Code (1)

agitoz/learning-label-initialization 공식 구현 pytorch

Tasks

ClassificationNode Classification

Similar Papers 제목 키워드 기반

Planner-Admissible Graph-PDE Value Extensions for Sparse Goal-Conditioned Planning

2026-05-18 · Shiheng Zhang arxiv

Sparse goal-conditioned planning with few cost-to-go labels can be viewed as a graph-PDE Dirichlet extension problem: extend sparse labels on a goal-dependent boundary to unlabelled graph vertices so that greedy rollouts…

On the Whitney near extension problem, BMO, alignment of data, best approximation in algebraic geometry, manifold learning and their beautiful connections: A modern treatment

2021-03-17 · Steven B. Damelin

This paper provides fascinating connections between several mathematical problems which lie on the intersection of several mathematics subjects, namely algebraic geometry, approximation theory, complex-harmonic analysis …

ClusteringDimensionality Reduction

Harmonic Extension

2015-09-22 · Zuoqiang Shi, Jian Sun, Minghao Tian

In this paper, we consider the harmonic extension problem, which is widely used in many applications of machine learning. We find that the transitional method of graph Laplacian fails to produce a good approximation of t…

BIG-bench Machine Learning

Weighted K-Harmonic Means Clustering: Convergence Analysis and Applications to Wireless Communications

2025-12-18 · Gourab Ghatak arxiv

We propose the \emph{weighted K-harmonic means} (WKHM) clustering algorithm, a regularized variant of K-harmonic means designed to ensure numerical stability while enabling soft assignments through inverse-distance weigh…

A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification

2016-10-14 · Shuai Zheng, Feiping Nie, Chris Ding, Heng Huang

Linear Discriminant Analysis (LDA) is a widely-used supervised dimensionality reduction method in computer vision and pattern recognition. In null space based LDA (NLDA), a well-known LDA extension, between-class distanc…

ClassificationDimensionality ReductionGeneral Classificationimage-classification+2