Publications related to Personalization

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Tatjana Nazaretsky, Tanja Christina Käser Jacober, Jibril Albachir Frej

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

Personalized Productive Engagement Recognition in Robot-Mediated Collaborative Learning

Barbara Bruno, Jauwairia Nasir

In this paper, we propose and compare personalized models for Productive Engagement (PE) recognition. PE is defined as the level of engagement that maximizes learning. Previously, in the context of robot-mediated collaborative learning, a framework of prod ...

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

Generalization and Personalization of Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Mood inference with mobile sensing data has been studied in ubicomp literature over the last decade. This inference enables context-aware and personalized user experiences in general mobile apps and valuable feedback and interventions in mobile health apps ...

ASSOC COMPUTING MACHINERY2022

Challenges and Opportunities in Integrating Interactive Chatbots into Code Review Exercises: A Pilot Case Study

Denis Gillet, Juan Carlos Farah, Adrian Christian Holzer

While chatbots are commonly used to support software developers with repetitive tasks, their use in programming education is still limited, particularly for students in non-technical domains. To better understand the potential for chatbots to support progr ...

IATED2022

Augmented Cooper test: Biomechanical contributions to endurance performance

Kamiar Aminian, Salil Apte, Vincent Gremeaux, Simone Troxler

Running mechanics are modifiable with training and adopting an economical running technique can improve running economy and hence performance. While field measurement of running economy is cumbersome, running mechanics can be assessed accurately and conven ...

FRONTIERS MEDIA SA2022

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Kamiar Aminian, Mathieu Pascal Falbriard, Abolfazl Soltani

The overground speed is a key component of running analysis. Today, most speed estimation wearable systems are based on GNSS technology. However, these devices can suffer from sparse communication with the satellites and have a high-power consumption. In t ...

2021

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

Identifying a Motivational Profile for Older Adults Towards Increased Physical Activity

Pearl Pu Faltings, Yuan Lu

Personalizing behavior change (BC) strategies to motivate increased physical activity is especially important for the diverse older adult population. However, there is a lack of knowledge about how to profile older users to most effectively personalize BC ...

2021

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

Printed Iontophoretic‐Integrated Wearable Microfluidic Sweat‐Sensing Patch for On‐Demand Point‐Of‐Care Sweat Analysis

Danick Briand, Silvia Demuru, Brince Paul Kunnel

In recent years, wearable epidermal sweat sensors have received extensive attention owing to their great potential to provide personalized information on the health status of individuals at the molecular level. For on‐demand medical analysis of sweat in se ...

Wiley2021

Body Dust: Well Beyond Wearable and Implantable Sensors

Sandro Carrara

Over the last 20 years, the field of Smart Dust has been proposed and demonstrated. Almost in the same period, implantable and wearable sensors for human monitoring have been actually successfully introduced in the market. The present research about Smart ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

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

Martin Jaggi, Mary-Anne Hartley, Sai Praneeth Reddy Karimireddy, 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

A Personalized Approach to Improve Walking Detection in Real-Life Settings: Application to Children with Cerebral Palsy

Kamiar Aminian, Anisoara Ionescu, Lena Carcreff, Stéphane Armand

Although many methods have been developed to detect walking by using body-worn inertial sensors, their performances decline when gait patterns become abnormal, as seen in children with cerebral palsy (CP). The aim of this study was to evaluate if fine-tuni ...

2019

Unified and Scalable Incremental Recommenders with Consumed Item Packs

Rachid Guerraoui, Rhicheek Patra

Recommenders personalize the web content using collaborative filtering to relate users (or items). This work proposes to unify user-based, item-based and neural word embeddings types of recommenders under a single abstraction for their input, we name Consu ...

Springer2019

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

Kamiar Aminian, Hooman Dejnabadi, Abolfazl Soltani, Martin Savary

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

Controlling Polarization in Personalization: An Algorithmic Framework

Nisheeth Vishnoi, Farnood Salehi, Laura Elisa Celis, Sayash Kapoor

Personalization is pervasive in the online space as it leads to higher efficiency for the user and higher revenue for the platform by individualizing the most relevant content for each user. However, recent studies suggest that such personalization can lea ...

ASSOC COMPUTING MACHINERY2019

Hardware/Software Co-Design and Reliability Analysis of Ultra-Low Power Biomedical Devices

Soumya Subhra Basu

Smart health monitoring devices, known as Wireless Body Sensor Nodes (WBSN) are transforming today's health-care landscape, shifting it from traditional hospital-based methods toward more personalized approaches. Their demand is ever-increasing in the mode ...

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