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Learning Urban Nightlife Routines from Mobile Data

Related publications (26)

Mirrored Langevin Dynamics

Volkan Cevher, Paul Thierry Yves Rolland, Ya-Ping Hsieh, Ali Kavis

We consider the problem of sampling from constrained distributions, which has posed significant challenges to both non-asymptotic analysis and algorithmic design. We propose a unified framework, which is inspired by the classical mirror descent, to derive ...

2018

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

Extremal attractors of Liouville copulas

Léo Raymond-Belzile

Liouville copulas introduced in McNeil and Ne lehova (2010) are asymmetric generalizations of the ubiquitous Archimedean copula class. They are the dependence structures of scale mixtures of Dirichlet distributions, also called Liouville distributions. In ...

2017

PARP inhibition protects against alcoholic and non-alcoholic steatohepatitis

Johan Auwerx, Zhou Zhou, Dongryeol Ryu, Karim Laurent Gariani, Wei Wang

Background & Aims: Mitochondria) dysfunction, oxidative stress, inflammation, and metabolic reprograming are crucial contributors to hepatic injury and subsequent liver fibrosis. Poly(ADP-ribose) polymerases (PARP) and their interactions with sirtuins play ...

Elsevier Science Bv2017

Online Inference in Bayesian Non-Parametric Mixture Models under Small Variance Asymptotics

Sylvain Calinon, Ajay Kumar Tanwani

Adapting statistical learning models online with large scale streaming data is a challenging problem. Bayesian non-parametric mixture models provide flexibility in model selection, however, their widespread use is limited by the computational overhead of e ...

2016

Data Summarization with Social Contexts

Karl Aberer, Xia Hu, Tian Guo, Hao Zhuang, Rameez Rahman

While social data is being widely used in various applications such as sentiment analysis and trend prediction, its sheer size also presents great challenges for storing, sharing and processing such data. These challenges can be addressed by data summariza ...

Assoc Computing Machinery2016