Search Results for author: Elif Vural

Found 13 papers, 1 papers with code

Learning Graph ARMA Processes from Time-Vertex Spectra

no code implementations14 Feb 2023 Eylem Tugce Guneyi, Berkay Yaldiz, Abdullah Canbolat, Elif Vural

The modeling of time-varying graph signals as stationary time-vertex stochastic processes permits the inference of missing signal values by efficiently employing the correlation patterns of the process across different graph nodes and time instants.

Learning Multi-Modal Nonlinear Embeddings: Performance Bounds and an Algorithm

no code implementations3 Jun 2020 Semih Kaya, Elif Vural

While many approaches exist in the literature to learn low-dimensional representations for data collections in multiple modalities, the generalizability of multi-modal nonlinear embeddings to previously unseen data is a rather overlooked subject.

General Classification Image Classification +4

Graph Domain Adaptation with Localized Graph Signal Representations

no code implementations7 Nov 2019 Yusuf Yigit Pilavci, Eylem Tugce Guneyi, Cemil Cengiz, Elif Vural

We estimate the unknown target labels by solving an optimization problem where the label information is transferred from the source graph to the target graph based on the prior that the projections of the label functions onto localized graph bases be similar between the source and the target graphs.

Domain Adaptation

Mask Combination of Multi-layer Graphs for Global Structure Inference

1 code implementation22 Oct 2019 Eda Bayram, Dorina Thanou, Elif Vural, Pascal Frossard

Structure inference is an important task for network data processing and analysis in data science.

Domain Adaptation on Graphs by Learning Graph Topologies: Theoretical Analysis and an Algorithm

no code implementations17 Dec 2018 Elif Vural

We first propose a theoretical analysis of domain adaptation on graphs and present performance bounds that characterize the target classification error in terms of the properties of the graphs and the data manifolds.

Domain Adaptation General Classification +1

Domain Adaptation on Graphs by Learning Aligned Graph Bases

no code implementations14 Mar 2018 Mehmet Pilanci, Elif Vural

Although the semi-supervised estimation of class labels is an ill-posed problem in general, in several applications it is possible to find a source graph on which the label function has similar frequency content to that on the target graph where the actual classification problem is defined.

Domain Adaptation General Classification

Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification

no code implementations28 Feb 2018 Jeremy Aghaei Mazaheri, Elif Vural, Claude Labit, Christine Guillemot

A multilevel tree-structured discriminative dictionary is learnt for each class, with a learning objective concerning the reconstruction errors of the image patches around the pixels over each class-representative dictionary.

Classification Denoising +3

Nonlinear Supervised Dimensionality Reduction via Smooth Regular Embeddings

no code implementations19 Oct 2017 Cem Ornek, Elif Vural

In this work, we build on recent theoretical results on the generalization performance of supervised manifold learning algorithms.

Supervised dimensionality reduction

A study of the classification of low-dimensional data with supervised manifold learning

no code implementations21 Jul 2015 Elif Vural, Christine Guillemot

Supervised manifold learning methods learn data representations by preserving the geometric structure of data while enhancing the separation between data samples from different classes.

Dimensionality Reduction General Classification +1

Geometry-Aware Neighborhood Search for Learning Local Models for Image Reconstruction

no code implementations6 May 2015 Julio Cesar Ferreira, Elif Vural, Christine Guillemot

Local learning of sparse image models has proven to be very effective to solve inverse problems in many computer vision applications.

Deblurring Denoising +3

Out-of-sample generalizations for supervised manifold learning for classification

no code implementations9 Feb 2015 Elif Vural, Christine Guillemot

Supervised manifold learning methods for data classification map data samples residing in a high-dimensional ambient space to a lower-dimensional domain in a structure-preserving way, while enhancing the separation between different classes in the learned embedding.

Classification General Classification

A Study of Image Analysis with Tangent Distance

no code implementations11 Jan 2014 Elif Vural, Pascal Frossard

As theoretical studies about the tangent distance algorithm have been largely overlooked, we present in this work a detailed performance analysis of this useful algorithm, which can eventually help its implementation.

Image Classification Image Registration

Analysis of Descent-Based Image Registration

no code implementations15 Feb 2013 Elif Vural, Pascal Frossard

We show that the area of this neighborhood increases at least quadratically with the smoothing filter size, which justifies the use of a smoothing step in image registration with local optimizers such as gradient descent.

Image Registration Translation

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