Publications associées à Aggregating information from the crowd : ratings, recommendations and predictions

E-Scan: Consuming Contextual Data with Model Plugins

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

2023

Dynamic Personalized Ranking

Jérémie Rappaz

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

EPFL2022

Positive and Negative Critiquing for VAE-based Recommenders

Boi Faltings, Diego Matteo Antognini

Providing explanations for recommended items allows users to refine the recommendations by critiquing parts of the explanations. As a result of revisiting critiquing from the perspective of multimodal generative models, recent work has proposed M&Ms-VAE, w ...

2022

Predictive Analysis of Errors During Robot-Mediated Gamified Training

Pierre Dillenbourg, Arzu Güneysu Özgür, Nihal Ezgi Yücetürk, Nevena Dresevic, Marija Katanic

This paper presents our approach to predicting future error-related events in a robot-mediated gamified phys- ical training activity for stroke patients. The ability to predict future error under such conditions suggests the existence of distinguishable fe ...

IEEE2022

A data-driven perspective on the colours of metal-organic frameworks

Luc Patiny, Seyedmohamad Moosavi, Berend Smit, Mehrdad Asgari, Christopher Patrick Ireland, Kevin Maik Jablonka

Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is often used to assess the success of a synthesis. However, predicting the colour of a materi ...

2021

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Elda Fischi Gomez, Cristina Granziera, Tom Hilbert, Muhamed Barakovic, Gian Franco Piredda, Erick Jorge Canales Rodriguez, Marco Pizzolato, Thomas Yu

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020

The use of texture-based radiomics CT analysis to predict outcomes in early-stage non-small cell lung cancer treated with stereotactic ablative radiotherapy

Adrien Raphaël Depeursinge, Pierre Starkov

Objective: Stereotactic ablative radiotherapy (SABR) is being increasingly used as a non-invasive treatment for early-stage non-small cell lung cancer (NSCLC). A non-invasive method to estimate treatment outcomes in these patients would be valuable, especi ...

BRITISH INST RADIOLOGY2019

Synchrotron MicroCT Reveals the Potential of the Dual Contrast Technique for Quantitative Assessment of Human Articular Cartilage Composition

Goran Lovric

Dual contrast micro computed tomography (CT) shows potential for detecting articular cartilage degeneration. However, the performance of conventional CT systems is limited by beam hardening, low image resolution (full-body CT), and long acquisition times ( ...

2020

Scaling Functional Synthesis and Repair

Emmanouil Koukoutos

Program synthesis was first proposed a few decades ago, but in the last decade it has gained increased momentum in the research community. The increasing complexity of software has dictated the urgent need for improved supporting tools that verify the soft ...

EPFL2019

Towards Scalable Personalization

Rhicheek Patra

The ever-growing amount of online information calls for Personalization. Among the various personalization systems, recommenders have become increasingly popular in recent years. Recommenders typically use collaborative filtering to suggest the most releva ...

EPFL2018

Microwave Imaging of Brain Stroke : Contributions to Modeling and Inverse Problem Resolution

Mina Bjelogrlic

Brain stroke is an age-related illness which has become a major issue in our ageing societies. Early diagnosis and treatment are of high importance for the full recovery of the patient, as reminded in Anglo-Saxon countries by the abbreviation FAST (Face, A ...

EPFL2018

Structuring Wikipedia Articles with Section Recommendations

Michele Catasta, Tiziano Piccardi, Robert West

Sections are the building blocks of Wikipedia articles. They enhance readability and can be used as a structured entry point for creating and expanding articles. Structuring a new or already existing Wikipedia article with sections is a hard task for human ...

ASSOC COMPUTING MACHINERY2018

Enhancing Social Media Platforms for Educational and Humanitarian Knowledge Sharing : Analytics, Privacy, Discovery, and Delivery Aspects

Andrii Vozniuk

Social media (SM) platforms have demonstrated their ability to facilitate knowledge sharing on the global scale. They are increasingly often employed in educational and humanitarian domains where, despite their general benefits, they expose challenges pecu ...

EPFL2017

Context-Dependent Privacy-Aware Photo Sharing based on Machine Learning

Touradj Ebrahimi, Lin Yuan, Joël Régis Theytaz

Photo privacy has raised a growing concern with the advancements of image analytics, face recognition, and deep learning techniques widely applied on social media. If properly deployed, these powerful techniques can in turn assist people in enhancing their ...

2017

Learning Explainable User Sentiment and Preferences for Information Filtering

Nikolaos Pappas

In the last decade, online social networks have enabled people to interact in many ways with each other and with content. The digital traces of such actions reveal people's preferences towards online content such as news or products. These traces often res ...

EPFL2016

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

Combining Content Analytics and Activity Tracking to Identify User Interests and Enable Knowledge Discovery

Denis Gillet, Andrii Vozniuk, Adrian Christian Holzer, Maria Jesus Rodriguez Triana

Finding relevant content is one of the core activities of users interacting with a content repository, be it knowledge workers using an organizational knowledge management system at a workplace or self-regulated learners collaborating in a learning environ ...

2016

A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT

Adrien Raphaël Depeursinge

This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated ...

Institute of Electrical and Electronics Engineers2016

Automating Grammar Comparison

Viktor Kuncak, Mikaël Mayer, Ravichandhran Kandhadai Madhavan

We consider from a practical perspective the problem of checking equivalence of context-free grammars. We present techniques for proving equivalence, as well as techniques for finding counter-examples that establish non-equivalence. Among the key building ...

2015

Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms

Jean-Pierre Hubaux, Igor Bilogrevic, Reza Shokri, Kévin Clément Huguenin, Stefan Mihaila

Location check-ins contain both geographical and semantic information about the visited venues, in the form of tags (e.g., “restaurant”). Such data might reveal some personal information about users beyond what they actually want to disclose, hence their p ...

2015