Publication

An Ordinal Latent Variable Model of Conflict Intensity

Publications associées (28)

Applications of Approximate Learning and Inference for Probabilistic Models

We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...

EPFL2017

Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation

Marina Boia

While artificial intelligence is successful in many applications that cover specific domains, for many commonsense problems there is still a large gap with human performance. Automated sentiment analysis is a typical example: while there are techniques tha ...

EPFL2016

Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data

Michel Bierlaire, Anna Fernández Antolín, Matthieu Marie Cochon de Lapparent

In this paper we extend the Multiple Indicator Solution (MIS) so that it can also be used to account for endogeneity when there are interactions between observed and unobserved factors in the specification of the utility function. We develop the theoretica ...

Elsevier Sci Ltd2016

Teaching Analytics: Towards Automatic Extraction of Orchestration Graphs Using Wearable Sensors

Pierre Dillenbourg, Kshitij Sharma, Luis Pablo Prieto Santos, Maria Jesus Rodriguez Triana

"Teaching analytics" is the application of learning analytics techniques to understand teaching and learning processes, and eventually enable supportive interventions. However, in the case of (often, half-improvised) teaching in face-to-face classrooms, su ...

Assoc Computing Machinery2016

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

Collaborative Recurrent Neural Networks for Dynamic Recommender Systems

Matthias Grossglauser, Lucas Maystre, Young Jun Ko

Modern technologies enable us to record sequences of online user activity at an unprecedented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating-prediction paradigm, ignoring temporal ...

2016

Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

Dimitrios Kyritsis, Min-Jung Yoo

This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messagi ...

Mdpi Ag2016

Word Embeddings for Natural Language Processing

Rémi Philippe Lebret

Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...

EPFL2016