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Publications associées (32)

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon

This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Bio-inspired Reflex System for Learning Visual Information for Resilient Robotic Manipulation

Josephine Anna Eleanor Hughes, Kai Christian Junge

Humans have an incredible sense of self-preservation that is both instilled, and also learned through experience. One system which contributes to this is the pain and reflex system which both minimizes damage through involuntary reflex ac- tions and also s ...

2022

The importance/role of education in chemical engineering

Thierry Meyer

Chemical engineering as a skilled profession depends on the competencies of the individuals practicing it. Formal teaching of chemical engineering at universities only started in the 19th century. Informally, the subject has been in existence at least sinc ...

2022

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

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

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

Smart Toys plus plus : Exploiting the Social Connectedness for Playing and Learning

Ayberk Özgür

Under the umbrella of smart toys, a myriad of interactive systems have addressed a variety of scenarios considering entertainment, education, sustainability, social and environmental learning through play. Tangibles and small toy robots prevail; but intera ...

ASSOC COMPUTING MACHINERY2021

Lifelong Machine Learning with Data Efficiency and Knowledge Retention

Fei Mi

Artificial intelligence (AI) and machine learning (ML) have become de facto tools in many real-life applications to offer a wide range of benefits for individuals and our society. A classic ML model is typically trained with a large-scale static dataset in ...

EPFL2021

Studying Alignment in Spontaneous Speech via Automatic Methods: How Do Children Use Task-specific Referents to Succeed in a Collaborative Learning Activity?

Barbara Bruno, Utku Norman

A dialogue is successful when there is alignment between the speakers, at different linguistic levels. In this work, we consider the dialogue occurring between interlocutors engaged in a collaborative learning task, and explore how performance and learning ...

2021

Robust Distributed Learning

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 t ...

EPFL2020

AlloHaptic: Robot-Mediated Haptic Collaboration for Learning Linear Functions*

Pierre Dillenbourg, Barbara Bruno, Wafa Monia Benkaouar Johal, Hala Khodr, Aditi Kothiyal, Soheil Kianzad

Collaborative learning appears in a joint intellectual efforts of individuals to understand an object of knowledge collectively. In their search for understanding the problems, meanings, and solutions, learners employ different multi-modal strategies. In t ...

IEEE2020

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