Publications related to Network Design via Core Detouring for Problems Without a Core

Approximating Steiner trees and forests with minimum number of Steiner points

Let R be a finite set of terminals in a convex metric space (M, d). We give approximation algorithms for problems of finding a minimum size set S subset of M of additional points such that the unit-disc graph G[R boolean OR S] of R boolean OR S satisfies s ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2018

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich, Anant Raj

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Matthias Grossglauser, Lucas Maystre

We address the problem of learning a ranking by using adaptively chosen pairwise comparisons. Our goal is to recover the ranking accurately but to sample the comparisons sparingly. If all comparison outcomes are consistent with the ranking, the optimal sol ...

2017

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

Compressive Spectral Clustering

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

Spectral clustering has become a popular technique due to its high performance in many contexts. It comprises three main steps: create a similarity graph between N objects to cluster, compute the first k eigenvectors of its Laplacian matrix to define a fea ...

2016

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes

Ting Zhu

The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of ...

EPFL2015

Analyte quantification with Comprehensive Two-Dimensional Gas Chromatography: Assessment of methods for baseline correction, peak delineation, and matrix effect elimination for real samples

Jeremy Samuel Arey, Jonas Gros, Saer Samanipour, Petros Dimitriou Christidis, Auréline Grange

Comprehensive two-dimensional gas chromatography (GC x GC) is used widely to separate and measure organic chemicals in complex mixtures. However, approaches to quantify analytes in real, complex samples have not been critically assessed. We quantified 7 PA ...

Elsevier2015

Full-wavefield modeling and reverse time migration of laser ultrasound data: A feasibility study

Thomas Emmanuel Blum

Laser ultrasound (LU) data acquired on cylindrical core samples effectively probe the physical properties of geologic materials. Although most LU analyses focus on estimating and inverting traveltimes of direct arrivals, it is important to recognize that L ...

2015

Too much success for recent groundbreaking epigenetic experiments

Gregory Francis

An article reporting statistical evidence for epigenetic transfer of learned behavior has important implications, if true. With random sampling, real effects do not always result in rejection of the null hypothesis, but the reported experiments were unifor ...

Genetics Society of America2014

Network Design via Core Detouring for Problems Without a Core

Graph Chatbot

Chat with Graph Search

Approximating Steiner trees and forests with minimum number of Steiner points

Safe Adaptive Importance Sampling

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Shapes from Pixels

Compressive Spectral Clustering

Random sampling of bandlimited signals on graphs

Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes

Analyte quantification with Comprehensive Two-Dimensional Gas Chromatography: Assessment of methods for baseline correction, peak delineation, and matrix effect elimination for real samples

Full-wavefield modeling and reverse time migration of laser ultrasound data: A feasibility study

Too much success for recent groundbreaking epigenetic experiments

Safe Adaptive Importance Sampling

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Compressive Spectral Clustering

Too much success for recent groundbreaking epigenetic experiments

Full-wavefield modeling and reverse time migration of laser ultrasound data: A feasibility study

Approximating Steiner trees and forests with minimum number of Steiner points

Analyte quantification with Comprehensive Two-Dimensional Gas Chromatography: Assessment of methods for baseline correction, peak delineation, and matrix effect elimination for real samples

Shapes from Pixels

Random sampling of bandlimited signals on graphs

Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes