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Publications associées (30)

Learning Urban Nightlife Routines from Mobile Data

Daniel Gatica-Perez, Thanh Trung Phan

The use of smartphone sensing for public health studies is appealing to understand routines. We present an approach to learn nightlife routines in a smartphone sensing dataset volunteered by 184 young people (1586 weekend nights with location data captured ...

ACM2020

Improved Credit Bounds for the Credit-Based Shaper in Time-Sensitive Networking

Jean-Yves Le Boudec, Eleni Stai, Ehsan Mohammadpour

In Time-Sensitive Networking (TSN), it is important to formally prove per-flow latency and backlog bounds. To this end, recent works have applied network calculus and obtained latency bounds from service curves. The latency component of such service curves ...

2019

Statistical Applications of Random Matrix Theory: Comparison of Two Populations

Rémy Mariétan

During the last twenty years, Random matrix theory (RMT) has produced numerous results that allow a better understanding of large random matrices. These advances have enabled interesting applications in the domain of communication. Although this theory can ...

EPFL2019

High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

Volkan Cevher, Paul Thierry Yves Rolland, Jonathan Mark Scarlett, Ilija Bogunovic

Bayesian optimization (BO) is a popular technique for sequential black-box function optimization, with applications including parameter tuning, robotics, environmental monitoring, and more. One of the most important challenges in BO is the development of a ...

2018

Range-based underwater target localization using an autonomous surface vehicle: Observability analysis

In the field of marine robotics, the problem of range based underwater target localization can be defined as that of localizing an unknown - fixed or moving - target from a surface vehicle called the tracker, using range information available about the tar ...

2018

Incorporating Human Expertise in Robot Motion Learning and Synthesis

Hang Yin

With the exponential growth of robotics and the fast development of their advanced cognitive and motor capabilities, one can start to envision humans and robots jointly working together in unstructured environments. Yet, for that to be possible, robots nee ...

EPFL2018

A preclinical model for identifying rats at risk of alcohol use disorder

Pierre Magistretti, Benjamin Boutrel

Alcohol use is one of the world's leading causes of death and disease, although only a small proportion of individuals develop persistent alcohol use disorder (AUD). The identification of vulnerable individuals prior to their chronic intoxication remains o ...

Springer Nature2017

Multi-task additive models with shared transfer functions based on dictionary learning

Pascal Frossard, Alhussein Fawzi

Additive models form a widely popular class of regression models which represent the relation between covariates and response variables as the sum of low-dimensional transfer functions. Besides flexibility and accuracy, a key benefit of these models is the ...

Institute of Electrical and Electronics Engineers2017

How to Measure the Killer Microsecond

Edouard Bugnion, Aikaterini Argyraki, Mia Primorac

Datacenter-networking research requires tools to both generate traffic and accurately measure latency and throughput. While hardware-based tools have long existed commercially, they are primarily used to validate ASICs and lack flexibility, e.g. to study n ...

Assoc Computing Machinery2017

Integrating geo-biodiversity features in the analysis of landscape patterns

Alexandre Buttler, Alexander Ludwig Johannes Peringer, Ioana Stoicescu

Spatial patterns are deeply linked to ecological processes and this relationship lies at the core of landscape ecology. In turn, landscape patterns are influenced by physical, biological and anthropogenic factors. The aim of this study was to explore how s ...

Elsevier Science Bv2017

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