Publication

Modeling annotator behaviors for crowd labeling

Publications associées (41)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Hydrometeor classification from two-dimensional video disdrometer data

Alexis Berne, Devis Tuia, Jacopo Grazioli, Marc Schneebeli Zeugin, Timothy Hugh Raupach, Samuel Monhart

The first hydrometeor classification technique based on two-dimensional video disdrometer (2DVD) data is presented. The method provides an estimate of the dominant hydrometeor type falling over time intervals of 60 s during precipitation, using the statist ...

European Geosciences Union2014

Beyond Knowledge Tracing. Modeling Skill Topologies with Bayesian Networks

Modeling and predicting student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for student modeling is Bayesian Knowledge Tracing (BKT). BKT models, however, lack the ability to describe the hierarchy and relationship ...

Springer2014

Detecting pedestrian destinations from ubiquitous digital footprint

Antonin Danalet

Walking is the key for efficient multimodal transport systems. Pedestrian infrastructures, such as railway stations, face congestion and need to understand flows. Data is required for models that can help managers in their infrastructure planning. In this ...

2013

Sequential Topic Models for Mining Recurrent Activities and their Relationships

Jagannadan Varadarajan

In this thesis, we address the analysis of activities from long term data logs with an emphasis on video recordings. Starting from simple words from video, we progressively build methods to infer higher level scene semantics. The main strategies used to ac ...

EPFL2012

Inferring activities from context measurements using Bayesian inference and random utility models

Michel Bierlaire, Gunnar Flötteröd, Ricardo Daniel Hurtubia González

Smartphones collect a wealth of information about their users. This includes GPS tracks and the MAC addresses of devices around the user, and it can go as far as taking visual and acoustic samples of the user's environment. We present a framework to identi ...

2009

Graphical display for annual climate-based daylight simulation

Marilyne Andersen, Magali Bodart

Due to daylight variability, a design cannot be thoroughly assessed using single-moment simulations, which is why we need dynamic performance metrics like Daylight Autonomy and Useful Daylight Illuminance. Going one step further, the annual variation in pe ...

2008

Covariance Kernels from Bayesian Generative Models

Matthias Seeger

We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task data using Bayesian techniques. We describe an implementation of this framework ...

2002

Mixture models for unsupervised and supervised learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

EPFL2000

Mixture Models for Unsupervised and Supervised Learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of all this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

IDIAP2000

Mixture Models for Unsupervised and Supervised Learning

École Polytechnique Fédérale de Lausanne, Computer Science Department2000