Publications related to The 3A Personalized, Contextual and Relation-based Recommender System

Machine learning-aided generative molecular design

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Tanja Christina Käser Jacober, Jibril Albachir Frej, Tatjana Nazaretsky

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

2023

Towards Novel Evaluation Methods for Social Dialog Systems

Ekaterina Svikhnushina

Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...

EPFL2023

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Hala Khodr

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

EPFL2023

Interactive Digital Engagement With Visual Artworks and Cultural Artefacts Enhances User Aesthetic Experiences in the Laboratory and Museum

Martin Vetterli, Loïc Arnaud Baboulaz, Christine Mohr, Pierre Gabioud

Digital technologies reshape the way we interact with our environment, including with artworks. Advanced computational imaging solutions allow having extremely high-resolution digital reproductions of artworks outside museums, presumably increasing artwork ...

TAYLOR & FRANCIS INC2022

TEE-based decentralized recommender systems: The raw data sharing redemption

Anne-Marie Kermarrec, Akash Balasaheb Dhasade, Nevena Dresevic, Rafael Pereira Pires

Recommenders are central in many applications today. The most effective recommendation schemes, such as those based on collaborative filtering (CF), exploit similarities between user profiles to make recommendations, but potentially expose private data. Fe ...

2022

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

p Recommender systems: Past, present, future

Pearl Pu Faltings

The origins of modern recommender systems date back to the early 1990s when they were mainly applied experimentally to personal email and information filtering. Today, 30 years later, personalized recommendations are ubiquitous and research in this highly ...

AMER ASSOC ARTIFICIAL INTELL2021

Advances in Bias-aware Recommendation on the Web

Mirko Marras

The goal of this tutorial is to provide the WSDM community with recent advances on the assessment and mitigation of data and algorithmic bias in recommender systems. We first introduce conceptual foundations, by presenting the state of the art and describi ...

ASSOC COMPUTING MACHINERY2021

Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations

Mirko Marras

Online education platforms play an increasingly important role in mediating the success of individuals' careers. Therefore, while building overlying content recommendation services, it becomes essential to guarantee that learners are provided with equal re ...

SPRINGER2022

Multi-Step Critiquing User Interface for Recommender Systems

Boi Faltings, Diego Matteo Antognini, Diana Andreea Petrescu

Recommendations with personalized explanations have been shown to increase user trust and perceived quality and help users make better decisions. Moreover, such explanations allow users to provide feedback by critiquing them. Several algorithms for recomme ...

ASSOC COMPUTING MACHINERY2021

Online Dating Quantification Practices: A Human-Machine Learning Process

Jessica Carolina Pidoux

The phenomenon of online dating via web and mobile phone applications involves several actors: graphical interfaces, developers, algorithmic systems for user matching, and users. These actors have been studied in parallel by the social sciences and by comp ...

EPFL2021

Weight Erosion: An Update Aggregation Scheme for Personalized Collaborative Machine Learning

Mary-Anne Hartley, Sai Praneeth Reddy Karimireddy, Martin Jaggi, Felix Hans Michel Grimberg

Background. In medicine and other applications, the copying and sharing of data is impractical for a range of well-considered reasons. With federated learning (FL) techniques, machine learning models can be trained on data spread across several locations w ...

Springer, Cham2020

Designing for the co-Orchestration of Social Transitions between Individual, Small-Group and Whole-Class Learning in the Classroom

Jennifer Kaitlyn Olsen

Educational technologies are often developed such that students work on specific social levels (e.g., individual, small group, whole class) at specific times. However, in the reality of the classroom, learning activities are not so cleanly divided, with tr ...

2020

Food Talks: visual and interaction principles for representing environmental and nutritional food information in augmented reality

Nicolas Henchoz, Delphine Ribes Lemay, Andreas Sonderegger, Emily Clare Groves

This user-centered design research project aimed to investigate visual and interaction principles for augmented reality (AR) in the context of environmental and nutritional food labelling. Nutritional information on existing food labels is often misunderst ...

2019

Learning How to Write with a Social Robot

Shruti Chandra

Learning handwriting is one of the main occupations for children in primary education. It is a complex skill that has been associated with children’s learning and development. Poor handwriting skills affect children negatively concerning their academic per ...

EPFL2019

Real-world gait speed estimation using wrist sensor: A personalized approach

Kamiar Aminian, Hooman Dejnabadi, Martin Savary, Abolfazl Soltani

Gait speed is an important parameter to characterize people's daily mobility. For real-world speed measurement, inertial sensors or Global Navigation Satellite System (GNSS) can be used on wrist, possibly integrated in a wristwatch. However, power consumpt ...

2019

The Reduced Immersed Method for Real-Time Fluid-Elastic Solid Interaction and Contact Simulation

Christopher Brandt

We introduce the Reduced Immersed Method (RIM) for the real-time simulation of two-way coupled incompressible fluids and elastic solids and the interaction of multiple deformables with (self-)collisions. Our framework is based on a novel discretization of ...

2019

Texture-driven parametric snakes for semi-automatic image segmentation

Michaël Unser, Adrien Raphaël Depeursinge, Anaïs Laure Marie-Thérèse Badoual

We present a texture-driven parametric snake for semi-automatic segmentation of a single and closed structure in an image. We propose a new energy functional that combines intensity and texture information. The two types of image information are balanced u ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2019

Discovering Interaction Patterns in Online Learning Environments : A Learning Analytics Research

Mina Shirvani Boroujeni

The increasing amount of data collected in online learning environments provides unique opportunities to better understand the learning processes in different educational settings. Learning analytics research aims at understanding and optimizing learning a ...

EPFL2018