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COLA: Decentralized Linear Learning

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Efficient Distributed Decision Trees for Robust Regression

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo

The availability of massive volumes of data and recent advances in data collection and processing platforms have motivated the development of distributed machine learning algorithms. In numerous real-world applications large datasets are inevitably noisy a ...

2016

The brain strategy for online learning

Ali H. Sayed, Stefan Vlaski, Bicheng Ying

Complexity is a double-edged sword for learning algorithms when the number of available samples for training in relation to the dimension of the feature space is small. This is because simple models do not sufficiently capture the nuances of the data set, ...

IEEE2016

Estimation in Functional Lagged Regression

Lukasz Kidzinski

The paper introduces a functional time series (lagged) regression model. The impulse-response coefficients in such a model are operators acting on a separable Hilbert space, which is the function space L-2 in applications. A spectral approach to the estima ...

Wiley-Blackwell2015

Regression Analysis of Building Energy Demand

This project attempts to tackle the problem of analysing the heat demand of build- ings at a large (district or city) scale. Specifically, building data from Geneva is used as a case study while building an environment with suitable tools for a continued a ...

2015

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Michael Lehning, Marc Parlange, Bettina Schaefli, Aurélien Gallice

The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments to assess the impact of human activities or climate chan ...

European Geosciences Union2015

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Frank Grégoire Jean de Morsier

The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

EPFL2014

Adaptation, Learning, and Optimization over Networks

Ali H. Sayed

This work deals with the topic of information processing over graphs. The presentation is largely self-contained and covers results that relate to the analysis and design of multi-agent networks for the distributed solution of optimization, adaptation, and ...

NOW Publishers2014

Diffusion estimation over cooperative networks with missing data

Ali H. Sayed

In many fields, and especially in the medical and social sciences and in various recommender systems, data are often gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they ...

IEEE2013

Damage detection using data-driven methods applied to moving-load responses

Ian Smith

Developed economies depend on complex and extensive systems of infrastructure to maintain economic prosperity and quality of life. In recent years, the implementation of Structural health monitoring (SHM) systems on full-scale bridges has increased. The go ...

Elsevier2013

Modeling and Optimizing Computer-Assisted Mathematics Learning in Children

Arithmetic abilities are essential in modern society. However, many children suffer from difficulties in learning mathematics, ranging from mild to severe numeracy problems. The prevalence of developmental dyscalculia is about 3%−6% in German speaking coun ...

ETH-Zürich2013