Publications related to A Fast Hadamard Transform for Signals with Sub-linear Sparsity in the Transform Domain

Learning Data Triage: Linear Decoding Works for Compressive MRI

The standard approach to compressive sampling considers recovering an unknown deterministic signal with certain known structure, and designing the sub-sampling pattern and recovery algorithm based on the known structure. This approach requires looking for ...

Ieee2016

Fast K-Means with Accurate Bounds

François Fleuret, James Peter Newling

We propose a novel accelerated exact

k

-means algorithm, which outperforms the current state-of-the-art low-dimensional algorithm in 18 of 22 experiments, running up to 3

\times

faster. We also propose a general improvement of existing state-of-the-art a ...

Idiap2016

Method and apparatus for low complexity spectral analysis of bio-signals

David Atienza Alonso, Andreas Peter Burg, Srinivasan Murali, Georgios Karakonstantis, Aviinaash Sankaranarayanan

A method and device for reducing the computational complexity of a processing algorithm, of a discrete signal, in particular of the spectral estimation and analysis of bio-signals, with minimum or no quality loss, which comprises steps of (a) choosing a do ...

2015

Method for determining the walsh-hadamard transform of n samples of a signal and apparatus for performing the same

Martin Vetterli, Robin Scheibler, Saeid Haghighatshoar

A computer-implemented method for determining the Walsh-Hadamard transform of N samples of a signal, comprises electing a plurality of hashing C matrices Σ1, . . . ΣC, computing C hashes of a particular length based at least on a hashing front end and the ...

2015

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method

Pierre Vandergheynst, Daniel Kressner, Nathanaël Perraudin, Ana Susnjara

Sinal-processing on graphs has developed into a very active field of research during the last decade. In particular, the number of applications using frames con-structed from graphs, like wavelets on graphs, has substantially increased. To attain scalabili ...

MATHICSE2015

Compressed Sensing of Memoryless Sources

Saeid Haghighatshoar

Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...

EPFL2014

Association Generation in Synthetic Population for Transportation Applications: Graph-Theoretic Solution

Michel Bierlaire, Bilal Farooq, Dimitrios Efthymiou, Paul Richard Anderson

The generation of synthetic populations through simulation methods is an important research topic and has a key application in agent-based modeling of transport and land use. The next step in this research area is the generation of complete synthetic house ...

Natl Acad Sciences2014

A Fast Hadamard Transform for Signals with Sub-linear Sparsity

Martin Vetterli, Robin Scheibler, Saeid Haghighatshoar

A new iterative low complexity algorithm has been presented for computing the Walsh-Hadamard transform (WHT) of an N dimensional signal with a K-sparse WHT, where N is a power of two and K = O(N^α), scales sub- linearly in N for some 0 < α < 1. Assuming a ...

2013

On some coloring problems in grids

Dominique de Werra

We study complexity issues related to some coloring problems in grids: we examine in particular the case of List coloring, of Precoloring extension and of (p, q)-List coloring, the case of List coloring in bipartite graphs where lists in the first part of ...

2013

Graph Matching for Adaptation in Remote Sensing

Devis Tuia

We present an adaptation algorithm focused on the description of the data changes under different acquisition conditions. When considering a source and a destination domain, the adaptation is carried out by transforming one data set to the other using an a ...

Ieee-Inst Electrical Electronics Engineers Inc2013

A Fast Hadamard Transform for Signals with Sub-linear Sparsity in the Transform Domain

Graph Chatbot

Chat with Graph Search

Learning Data Triage: Linear Decoding Works for Compressive MRI

Fast K-Means with Accurate Bounds

Method and apparatus for low complexity spectral analysis of bio-signals

Method for determining the walsh-hadamard transform of n samples of a signal and apparatus for performing the same

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method

Compressed Sensing of Memoryless Sources

Association Generation in Synthetic Population for Transportation Applications: Graph-Theoretic Solution

A Fast Hadamard Transform for Signals with Sub-linear Sparsity

On some coloring problems in grids

Graph Matching for Adaptation in Remote Sensing

On some coloring problems in grids

Learning Data Triage: Linear Decoding Works for Compressive MRI

Method for determining the walsh-hadamard transform of n samples of a signal and apparatus for performing the same

Method and apparatus for low complexity spectral analysis of bio-signals

Fast K-Means with Accurate Bounds

Compressed Sensing of Memoryless Sources

A Fast Hadamard Transform for Signals with Sub-linear Sparsity

Association Generation in Synthetic Population for Transportation Applications: Graph-Theoretic Solution

Graph Matching for Adaptation in Remote Sensing

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method