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Composite Kernel Learning

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Machine-Learning of Atomic-Scale Properties Based on Physical Principles

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We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear fun ...

Springer International Publishing2020

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A smart campus provides students who are geographically scattered with online tools to get access to learning resources and laboratories. Although these remote laboratories have the potential and capabilities to implement different learning experiments, mo ...

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Training Channel Selection for Learning-based 1-bit Precoding in Massive MU-MIMO

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Sitian Li

Learning-based algorithms have gained great popularity in communications since they often outperform even carefully engineered solutions by learning from training samples. In this paper, we show that the selection of appropriate training examples can be im ...

IEEE2020

Learning Approach to Delineation of Curvilinear Structures in 2D and 3D Images

Agata Justyna Mosinska

Detection of curvilinear structures has long been of interest due to its wide range of applications. Large amounts of imaging data could be readily used in many fields, but it is practically not possible to analyze them manually. Hence, the need for automa ...

EPFL2019

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

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Learner-Computer Interaction (LCI) research addresses the design, development and use of interactive technologies to support and amplify human learning. LCI is based on the rationale that learning while interacting with technology is a complex, multi-layer ...

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Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

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Modern data-center network operating systems rely on proprietary user-space daemons wrapping SDKs from switch vendors. Linux-based variants of these operating systems have benefited from increasing and simplified dataplane offloading support in recent year ...

2018

Encapsulating Online Labs in Structured Learning Spaces

Denis Gillet, Juan Carlos Farah

This paper builds on the results of European research projects to support STEM education with online labs. We present Integrated Interaction Apps as a means to support learning activities centered on online labs. We then show how these apps, labs and other ...

2018

Editorial

Maria Jesus Rodriguez Triana

Learning is a complex, mostly invisible process that happens across spaces, occurring in the physical world but also increasingly in virtual worlds or web-based spaces. In order to explore what happens in such blended learning experience, there is a need ...

CEUR2017

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

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In this paper, we consider the problem of sequentially optimizing a black-box function

f

based on noisy samples and bandit feedback. We assume that

f

is smooth in the sense of having a bounded norm in some reproducing kernel Hilbert space (RKHS), yield ...

2017