Publications related to On near-uniform URL sampling

WEBGRAPH: Capturing Advertising and Tracking Information Flows for Robust Blocking

Carmela González Troncoso, Sandra Deepthy Siby

Users rely on ad and tracker blocking tools to protect their privacy. Unfortunately, existing ad and tracker blocking tools are susceptible to mutable advertising and tracking content. In this paper, we first demonstrate that a state-of-the-art ad and trac ...

USENIX ASSOC2022

Rethinking Sampling in Parallel MRI: A Data-Driven Approach

Volkan Cevher, Baran Gözcü, Thomas Sanchez

In the last decade, Compressive Sensing (CS) has emerged as the most promising, model-driven approach to accelerate MRI scans. CS relies on the key sparsity assumption and proposes random sampling for data acquisition. The practical CS approaches in MRI em ...

IEEE2019

A Graph-structured Dataset for Wikipedia Research

Pierre Vandergheynst, Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud

Wikipedia is a rich and invaluable source of information. Its central place on the Web makes it a particularly interesting object of study for scientists. Researchers from different domains used various complex datasets related to Wikipedia to study langua ...

ACM2019

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, i.e., independent of the graph structure, and its performa ...

Elsevier2018

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

Object Detection with Active Sample Harvesting

Olivier Canévet

The work presented in this dissertation lies in the domains of image classification, object detection, and machine learning. Whether it is training image classifiers or object detectors, the learning phase consists in finding an optimal boundary between po ...

EPFL2017

Object Detection with Active Sample Harvesting

Olivier Canévet

The work presented in this dissertation lies in the domains of image classification, object detection, and machine learning. Whether it is training image classifiers or object detectors, the learning phase consists in finding an optimal boundary between po ...

École Polytechnique Fédérale de Lausanne2017

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Matthieu Martin Jean-André Simeoni

Estimating intensity fields of stochastic phenomenons is of crucial interest in many scientific applications. Typical experimental setups involve an acquisition system, that subsequently filters and samples the probed intensity field. This equivalently def ...

2016

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web

Joshua Evan Auerbach, Sebastian Risi, Jason Yosinski

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from ...

Mit Press2016

On near-uniform URL sampling

Graph Chatbot

Chat with Graph Search

WEBGRAPH: Capturing Advertising and Tracking Information Flows for Robust Blocking

Rethinking Sampling in Parallel MRI: A Data-Driven Approach

A Graph-structured Dataset for Wikipedia Research

Random sampling of bandlimited signals on graphs

Safe Adaptive Importance Sampling

Object Detection with Active Sample Harvesting

Object Detection with Active Sample Harvesting

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web

WEBGRAPH: Capturing Advertising and Tracking Information Flows for Robust Blocking

Safe Adaptive Importance Sampling

Object Detection with Active Sample Harvesting

A Graph-structured Dataset for Wikipedia Research

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Random sampling of bandlimited signals on graphs

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web

Rethinking Sampling in Parallel MRI: A Data-Driven Approach

Object Detection with Active Sample Harvesting

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source