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09/04/2023
Locally Stationary Graph Processes
Stationary graph process models are commonly used in the analysis and in...
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02/14/2023
Learning Graph ARMA Processes from Time-Vertex Spectra
The modeling of time-varying graph signals as stationary time-vertex sto...
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06/03/2020
Learning Multi-Modal Nonlinear Embeddings: Performance Bounds and an Algorithm
While many approaches exist in the literature to learn representations f...
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11/07/2019
Graph Domain Adaptation with Localized Graph Signal Representations
In this paper we propose a domain adaptation algorithm designed for grap...
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10/22/2019
Mask Combination of Multi-layer Graphs for Global Structure Inference
Structure inference is an important task for network data processing and...
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12/17/2018
Domain Adaptation on Graphs by Learning Graph Topologies: Theoretical Analysis and an Algorithm
Traditional machine learning algorithms assume that the training and tes...
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03/14/2018
Domain Adaptation on Graphs by Learning Aligned Graph Bases
We propose a method for domain adaptation on graphs. Given sufficiently ...
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02/28/2018
Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification
Sparse representations using overcomplete dictionaries have proved to be...
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10/19/2017
Nonlinear Supervised Dimensionality Reduction via Smooth Regular Embeddings
The recovery of the intrinsic geometric structures of data collections i...
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05/06/2015
Geometry-Aware Neighborhood Search for Learning Local Models for Image Reconstruction
Local learning of sparse image models has proven to be very effective to...
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02/09/2015
Out-of-sample generalizations for supervised manifold learning for classification
Supervised manifold learning methods for data classification map data sa...
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01/11/2014
A Study of Image Analysis with Tangent Distance
The computation of the geometric transformation between a reference and ...
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12/23/2011
Learning Smooth Pattern Transformation Manifolds
Manifold models provide low-dimensional representations that are useful ...
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12/23/2011
