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Distributed Meta-Learning with Networked Agents

Ali H. Sayed, Stefan Vlaski, Mert Kayaalp

Meta-learning aims to improve efficiency of learning new tasks by exploiting the inductive biases obtained from related tasks. Previous works consider centralized or federated architectures that rely on central processors, whereas, in this paper, we propos ...

EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP2021

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

Learning a Unified Blind Image Quality Metric via On-Line and Off-Line Big Training Instances

Daniel Thalmann

In this work, we resolve a big challenge that most current image quality metrics (IQMs) are unavailable across different image contents, especially simultaneously coping with natural scene (NS) images or screen content (SC) images. By comparison with exist ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Broccoli: Sprinkling Lightweight Vocabulary Learning into Everyday Information Diets

Arnaud Pierre Jean Miribel, Robert West, Lars Henning Klein

The learning of a new language remains to this date a cognitive task that requires considerable diligence and willpower, recent advances and tools notwithstanding. In this paper, we propose Broccoli, a new paradigm aimed at reducing the required effort by ...

ASSOC COMPUTING MACHINERY2020

Learning and leveraging shared domain semantics to counteract visual domain shifts

Róger Bermúdez Chacón

One of the main limitations of artificial intelligence today is its inability to adapt to unforeseen circumstances. Machine Learning (ML), due to its data-driven nature, is particularly susceptible to this. ML relies on observations in order to learn impli ...

EPFL2020

TIP: Tangible e-Ink Paper Manipulatives for Classroom Orchestration

Pierre Dillenbourg, Wafa Monia Benkaouar Johal, Ayberk Özgür, Hala Khodr

While digital tools are more and more used in classrooms, teachers' common practice remains to use photocopied paper documents to share and collect learning exercises from their students. With the Tangible e-Ink Paper (TIP) system, we aim to explore the us ...

ACM2019

The dynamics of motor learning through the formation of internal models

Camilla Pierella

A medical student learning to perform a laparoscopic procedure or a recently paralyzed user of a powered wheelchair must learn to operate machinery via interfaces that translate their actions into commands for an external device. Since the user’s actions a ...

2019

MMKG: Multi-modal Knowledge Graphs

Alberto Garcia Duran

We present Mmkg, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KGs. Therefore, multi-relational link prediction and entity matching communiti ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

On the Use of Gaze as a Measure for Performance in a Visual Exploration Task

Pierre Dillenbourg, Jennifer Kaitlyn Olsen, Catharine Regina Monika Maria Oertel Genannt Bierbach

Visual exploration skill acquisition is important for many vocational professions, yet many apprentices struggle to acquire these skills, impacting both their grades and practical work. Traditionally, the learning of visual skills is facilitated through ex ...

Springer2019

Analytics for learning design: A layered framework and tools

Maria Jesus Rodriguez Triana

The field of learning design studies how to support teachers in devising suitable activities for their students to learn. The field of learning analytics explores how data about students' interactions can be used to increase the understanding of learning e ...

2019