Concept

Personalization

Related publications (59)

Body Dust: Well Beyond Wearable and Implantable Sensors

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

Privacy-preserving and Personalized Federated Machine Learning for Medical Data

Felix Hans Michel Grimberg

The federated learning setting is prone to suffering from non-identically distributed data across participating agents. This gives rise to the task of model personalization, where agents collaborate to train several different machine learning models instea ...

2020

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

Robust Distributed Learning and Robust Learning Machines (Research Statement)

El Mahdi El Mhamdi

Whether it occurs in artificial or biological substrates, {\it learning} is a {distributed} phenomenon in at least two aspects. First, meaningful data and experiences are rarely found in one location, hence {\it learners} have a strong incentive to work to ...

2019

Controlling Polarization in Personalization: An Algorithmic Framework

Nisheeth Vishnoi, Laura Elisa Celis, Farnood Salehi, 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

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

Ten Years of Research on Intelligent Educational Games for Learning Spelling and Mathematics

In this article, we present our findings from ten years of research on intelligent educational games. We discuss the architecture of our training environments for learning spelling and mathematics, and specifically focus on the representation of the conten ...

2018

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