Publications related to Analyse I (partie 5) : Fonctions continues et fonctions dérivables, la fonction dérivée

Figlearn: Filter And Graph Learning Using Optimal Transport

Pascal Frossard, Mireille El Gheche, Matthias Minder, Zahra Farsijani

In many applications, a dataset can be considered as a set of observed signals that live on an unknown underlying graph structure. Some of these signals may be seen as white noise that has been filtered on the graph topology by a graph filter. Hence, the k ...

IEEE2021

Partition and Code: learning how to compress graphs

Michael Bronstein, Andreas Loukas, Nikolaos Karalias, Georgios Bouritsas

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant patterns. On the other ...

2021

Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations

Mrinmaya Sachan, Mattia Atzeni

Text-based games (TBGs) have emerged as useful benchmarks for evaluating progress at the intersection of grounded language understanding and reinforcement learning (RL). Recent work has proposed the use of external knowledge to improve the efficiency of RL ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

A decomposition of multicorrelation sequences for commuting transformations along primes

Florian Karl Richter

A decomposition of multicorrelation sequences for commuting transformations along primes, Discrete Analysis 2021:4, 27 pp. Szemerédi's theorem asserts that for every positive integer

k

and every

\delta>0

there exists

n

such that every subset of ${1, ...

2021

Tree in Tree: from Decision trees to Decision Graphs

Mahsa Shoaran, Bingzhao Zhu

Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional dec ...

Curran Associates, Inc, (NIPS '21: Proceedings of the 35th International Conference on Neural Information Processing Systems)2021

How Florist Apprentices Explore Bouquet Designs: Supporting Design Space Exploration for Vocational Students

Pierre Dillenbourg, Kevin Gonyop Kim, Catharine Regina Monika Maria Oertel Genannt Bierbach

Context: Exploring the design space is an important process in a design task. In this study, we considered design space exploration for the learners in vocational education and training (VET). The goal of the study was to investigate how they explore the d ...

2021

The GOGREEN survey: dependence of galaxy properties on halo mass a z > 1 and implications for environmental quenching

Pascale Jablonka, Hung-Hsu Chan

We use photometric redshifts and statistical background subtraction to measure stellar mass functions in galaxy group-mass (4.5-8 x 10(13) M-circle dot) haloes at 1 < z < 1.5. Groups are selected from COSMOS and SXDF, based on X-ray imaging and sparse spec ...

OXFORD UNIV PRESS2021

ON WAVEFRONT ABERRATIONS IN ASYMMETRIC AND MULTIPLE APERTURE OPTICAL SYSTEMS

Alessandro Grosso

The present work deals with monochromatic wavefront aberrations in optical systems without symmetries. The treatment begins with a class of systems characterized by misaligned spherical surfaces whose behavior is analyzed using the wavefront aberration exp ...

EPFL2021

A New Channel-Base Lightning Current Formula With Analytically Adjustable Parameters

Farhad Rachidi-Haeri

The article provides a new channel-based current function, which aims at faithfully reproducing the salient parameters of lightning currents. All the model parameters can be set in a fully analytical way, guaranteeing the possibility of changing them (acco ...

2021

Deterministic error bounds for kernel-based learning techniques under bounded noise

Colin Neil Jones, Paul Scharnhorst, Emilio Maddalena

We consider the problem of reconstructing a function from a finite set of noise-corrupted samples. Two kernel algorithms are analyzed, namely kernel ridge regression and epsilon-support vector regression. By assuming the ground-truth function belongs to th ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Analyse I (partie 5) : Fonctions continues et fonctions dérivables, la fonction dérivée

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Figlearn: Filter And Graph Learning Using Optimal Transport

Partition and Code: learning how to compress graphs

Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations

A decomposition of multicorrelation sequences for commuting transformations along primes

Tree in Tree: from Decision trees to Decision Graphs

How Florist Apprentices Explore Bouquet Designs: Supporting Design Space Exploration for Vocational Students

The GOGREEN survey: dependence of galaxy properties on halo mass a z > 1 and implications for environmental quenching

ON WAVEFRONT ABERRATIONS IN ASYMMETRIC AND MULTIPLE APERTURE OPTICAL SYSTEMS

A New Channel-Base Lightning Current Formula With Analytically Adjustable Parameters

Deterministic error bounds for kernel-based learning techniques under bounded noise

The GOGREEN survey: dependence of galaxy properties on halo mass a z > 1 and implications for environmental quenching

ON WAVEFRONT ABERRATIONS IN ASYMMETRIC AND MULTIPLE APERTURE OPTICAL SYSTEMS

Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations

A decomposition of multicorrelation sequences for commuting transformations along primes

Figlearn: Filter And Graph Learning Using Optimal Transport

Tree in Tree: from Decision trees to Decision Graphs

How Florist Apprentices Explore Bouquet Designs: Supporting Design Space Exploration for Vocational Students

A New Channel-Base Lightning Current Formula With Analytically Adjustable Parameters

Deterministic error bounds for kernel-based learning techniques under bounded noise

Partition and Code: learning how to compress graphs