Personne
Mohammadjavad Faraji
Cette personne n’est plus à l’EPFL
Publications associées (6)
A Multiscale Pyramid Transform for Graph Signals
Pierre Vandergheynst, David Shuman, Mohammadjavad Faraji
Multiscale transforms designed to process analog and discrete-time signals and images cannot be directly applied to analyze high-dimensional data residing on the vertices of a weighted graph, as they do not capture the intrinsic topology of the graph data ...
Institute of Electrical and Electronics Engineers2016Learning with Surprise
Everybody knows what it feels to be surprised. Surprise raises our attention and is crucial for learning. It is a ubiquitous concept whose traces have been found in both neuroscience and machine learning. However, a comprehensive theory has not yet been de ...
EPFL2016Balancing New Against Old Information: The Role of Surprise
Wulfram Gerstner, Kerstin Preuschoff, Mohammadjavad Faraji
Surprise is a widely used concept describing a range of phenomena from unexpected events to behavioral responses. We propose a measure of surprise, to arrive at a new framework for surprise-driven learning. There are two components to this framework: (i) a ...
Public Library of Science2016A Laplacian pyramid scheme in graph signal processing
In this report we extend the ideas behind classical multiscale signal processing techniques in order to analyze data residing on graphs. In particular, we extend the notions of filtering, downsampling, and upsampling to functions defined on graphs. We then ...
2011Semi-Supervised Learning with Spectral Graph Wavelets
Pierre Vandergheynst, David Shuman, Mohammadjavad Faraji
We consider the transductive learning problem when the labels belong to a continuous space. Through the use of spectral graph wavelets, we explore the benefits of multiresolution analysis on a graph constructed from the labeled and unlabeled data. The spec ...
2011Constructing and decoding GWBE codes using Kronecker products
Mohammadjavad Faraji, Pedram Pad
In this letter, we introduce a novel method for constructing large size generalized Welch bound equality (GWBE) matrices. This method can also be used for the construction of large WBE matrices. The advantage of this method is its low complexity for constr ...
Institute of Electrical and Electronics Engineers2010