Concept

Learning to rank

Publications associées (133)

A tutorial on machine learning in educational science

Popularity of massive online open courses (MOOCs) allowed educational researchers to address problems which were not accessible few years ago. Although classical statistical techniques still apply, large datasets allow us to discover deeper patterns and to ...

2015

Camera-based estimation of student's attention in class

Mirko Raca

Two essential elements of classroom lecturing are the teacher and the students. This human core can easily be lost in the overwhelming list of technological supplements aimed at improving the teaching/learning experience. We start from the question of whet ...

EPFL2015

Metric Learning with Rank and Sparsity Constraints

Volkan Cevher, Baran Gözcü, Bubacarr Bah

Choosing a distance preserving measure or metric is fun- damental to many signal processing algorithms, such as k- means, nearest neighbor searches, hashing, and compressive sensing. In virtually all these applications, the efficiency of the signal process ...

Ieee2014

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Frank Grégoire Jean de Morsier

The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

EPFL2014

Semi-Supervised Method for Multi-Category Emotion Recognition in Tweets

Pearl Pu Faltings, Claudiu-Cristian Musat, Valentina Sintsova

Each tweet is limited to 140 characters. This constraint surprisingly makes Twitter a more spontaneous platform to express our emotions. Detecting emotions and correctly classifying them automatically is an increasingly important task if we want to underst ...

2014

Weakly Supervised Object Segmentation with 004 dwaeConvolutional Neural Networks

Ronan Collobert, Pedro Henrique Oliveira Pinheiro

Can a machine learn how to segment different objects in real world images without having any prior knowledge about the delineation of the classes? In this paper, we demonstrate that this task is indeed possible. We address the problem by training a Convolu ...

Idiap2014

A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services

James Richard Larus

Datacenter workloads demand high computational capabilities, flexibility, power efficiency, and low cost. It is challenging to improve all of these factors simultaneously. To advance datacenter capabilities beyond what commodity server designs can provide, ...

ACM/IEEE2014

An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages

Marcel Salathé

The role of social media as a source of timely and massive information has become more apparent since the era of Web 2.0.Multiple studies illustrated the use of information in social media to discover biomedical and health-related knowledge.Most methods pr ...

Elsevier2014

Separable Filter Learning with Tensor Decomposition

Bugra Tekin

Learned image features can provide great accuracy in many Computer Vision tasks. However, when the convolution filters used to learn image features are numerous and not separable, feature extraction becomes computationally de- manding and impractical to us ...

2013

Learning Separable Filters with Shared Parts

Bugra Tekin

2013

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