Publications associées à Filtrage bayésien du spam

DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications

Convolutional Neural Networks (CNNs) are a cornerstone of the Deep Learning toolbox and have led to many breakthroughs in Artificial Intelligence. So far, these neural networks (NNs) have mostly been developed for regular Euclidean domains such as those su ...

ELSEVIER SCIENCE BV2019

A new method for reducing local heat transfer data in multimicrochannel evaporators

John Richard Thome, Navid Borhani, Nicolas Lamaison, Houxue Huang

Measuring the strong local variation in heat transfer coefficients in multi-microchannel evaporators is related to the inverse heat conduction problem (IHCP). As the local flow heat transfer coefficients change greatly in magnitude from single-phase liquid ...

Elsevier France-Editions Scientifiques Medicales Elsevier2017

Artificial immune system for the Internet

Slavisa Sarafijanovic

We investigate the usability of the Artificial Immune Systems (AIS) approach for solving selected problems in computer networks. Artificial immune systems are created by using the concepts and algorithms inspired by the theory of how the Human Immune Syste ...

EPFL2008

Improving Digest-Based Collaborative Spam Detection

Jean-Yves Le Boudec, Slavisa Sarafijanovic

Spam is usually sent in bulk. A bulk mailing consists of many copies of the same original spam message, each sent to a different recipient. The copies are usually obfuscated, i.e. modified a bit in order to look different from each other. In collaborative ...

2008

Resolving FP-TP Conflict in Digest-Based Collaborative Spam Detection by Use of Negative Selection Algorithm

Jean-Yves Le Boudec, Slavisa Sarafijanovic

A well-known approach for collaborative spam filtering is to determine which emails belong to the same bulk, e.g. by exploiting their content similarity. This allows, after observing an initial portion of a bulk, for the bulkiness scores to be assigned to ...

2008

Artificial Immune System For Collaborative Spam Filtering

Jean-Yves Le Boudec, Slavisa Sarafijanovic

Artificial immune systems (AIS) use the concepts and algorithms inspired by the theory of how the human immune system works. This document presents the design and initial evaluation of a new artificial immune system for collaborative spam filtering. Collab ...

Springer Verlag2008

AntispamLab - A Tool for Realistic Evaluation of Email Spam Filters

Jean-Yves Le Boudec, Slavisa Sarafijanovic, Raphaël Naefen, Luis Hernandez

The existing tools for testing spam filters evaluate a filter instance by simply feeding it with a stream of emails, possibly also providing a feedback to the filter about the correctness of the detection. In such a scenario the evaluated filter is disconn ...

2007