Concept

Naive Bayes spam filtering

Related publications (27)

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

Optinal Source-Based Filtering of Malicious Traffic

In this paper, we consider the problem of blocking malicious traffic on the Internet via source-based filtering. In particular, we consider filtering via access control lists (ACLs): These are already available at the routers today, but are a scarce resour ...

2012

Discovering relevant spatial filterbanks for VHR image classification

Devis Tuia

In very high resolution (VHR) image classification it is common to use spatial filters to enhance the discrimination among landuses related to similar spectral properties but different spatial characteristics. However, the filters types that can be used ar ...

2012

Efficient monitoring of personalized hot news over Web 2.0 streams

Karl Aberer, Sebastian Michel, Parisa Haghani

Web 2.0 streams, like blog postings, microblogging tweets, or RSS feeds from online communities, offer a wealth of latest news about real-world events and societal discussion. From a user’s perspective, it becomes harder and harder to get a decent overview ...

2012

Collaborative learning of mixture models using diffusion adaptation

Ali H. Sayed

In large ad-hoc networks, classification tasks such as spam filtering, multi-camera surveillance, and advertising have been traditionally implemented in a centralized manner by means of fusion centers. These centers receive and process the information that ...

IEEE2011

Face Detection using Ferns

Sébastien Marcel, Venkatesh Bala Subburaman

This paper discusses the use of ferns (a set of binary features) for face detection. The binary feature used here is the sign of pixel intensity difference. Ferns were first introduced for keypoint recognition and showed good performance, and improving the ...

Idiap2011

Signaling and Reciprocity

Wojciech Galuba

Complex networks exist for a number of purposes. The neural, metabolic and food networks ensure our survival, while the social, economic, transportation and communication networks allow us to prosper. Independently of the purposes and particularities of th ...

EPFL2011

Digital Suppression of Spurious PLL Tones in A/D Converters

Ali H. Sayed

In a nonideal PLL circuit, leakage of the reference signal into the control line produces spurious tones. When the distorted PLL signal is used in an analog-to-digital converter (ADC), it injects the spurious tones into the sampled data. These distortions ...

IEEE2011

Outtweeting the Twitterers - Predicting Information Cascades in Microblogs

Karl Aberer, Dipanjan Chakraborty, Wojciech Galuba, Zoran Despotovic

Microblogging sites are a unique and dynamic Web 2.0 communication medium. Understanding the information flow in these systems can not only provide better insights into the underlying sociology, but is also crucial for applications such as content ranking, ...

2010

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.