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Graph Representation Learning with Optimal Transport: Analysis and Applications

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Ten Years of Research on Intelligent Educational Games for Learning Spelling and Mathematics

In this article, we present our findings from ten years of research on intelligent educational games. We discuss the architecture of our training environments for learning spelling and mathematics, and specifically focus on the representation of the conten ...

2018

Ten Years of Research on Intelligent Educational Games for Learning Spelling and Mathematics

2018

Graph-based structures in data science

Nathanaël Perraudin

State-of-the-art data analysis tools have to deal with high-dimensional data. Fortunately, the inherent dimensionality of data is often much smaller, as it has an internal structure limiting its degrees of freedom. In most cases, this structure can be appr ...

EPFL2017

Everything You Always Wanted to Know about Multicore Graph Processing but Were Afraid to Ask

Willy Zwaenepoel, Baptiste Joseph Eustache Lepers, Jasmina Malicevic

Graph processing systems are used in a wide variety of fields, ranging from biology to social networks, and a large number of such systems have been described in the recent literature. We perform a systematic comparison of various techniques proposed to sp ...

USENIX Association2017

Efficient Online Processing for Advanced Analytics

Mohamed Elsayed Mohamed Ahmed El Seidy

With the advent of emerging technologies and the Internet of Things, the importance of online data analytics has become more pronounced. Businesses and companies are adopting approaches that provide responsive analytics to stay competitive in the global ma ...

EPFL2017

Geometric deep learning: going beyond Euclidean data

Pierre Vandergheynst, Michael Bronstein

Many signal processing problems involve data whose underlying structure is non-Euclidean, but may be modeled as a manifold or (combinatorial) graph. For instance, in social networks, the characteristics of users can be modeled as signals on the vertices of ...

2017

Graph-Based Classification of Omnidirectional Images

Pascal Frossard, Renata Khasanova

Omnidirectional cameras are widely used in such areas as robotics and virtual reality as they provide a wide field of view. Their images are often processed with classical methods, which might unfortunately lead to non-optimal solutions as these methods ar ...

2017

Learning heat diffusion graphs

Pascal Frossard, Daniel Kressner, Xiaowen Dong

Effective information analysis generally boils down to properly identifying the structure or geometry of the data, which is often represented by a graph. In some applications, this structure may be partly determined by design constraints or pre-determined ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Large Scale Graph Learning from Smooth Signals

Nathanaël Perraudin, Vasilis Kalofolias

Graphs are a prevalent tool in data science, as they model the inherent structure of the data. They have been used successfully in unsupervised and semi-supervised learning. Typically they are constructed either by connecting nearest samples, or by learnin ...

2017

Improving speaker turn embedding by crossmodal transfer learning from face embedding

Jean-Marc Odobez

Learning speaker turn embeddings has shown considerable improvement in situations where conventional speaker modeling approaches fail. However, this improvement is relatively limited when compared to the gain observed in face embedding learning, which has ...

2017