Concept

Fléau de la dimension

Publications associées (331)

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Distributed user profiling via spectral methods

Dan-Cristian Tomozei

User profiling is a useful primitive for constructing personalised services, such as content recommendation. In the present paper we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local informatio ...

2014

Successive Refinement of Gaussian Projections

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

Successive refinement is a technique to encode a source iteratively, improving the distortion at each step. If the code rates of all steps combined can be as efficient as coding only for the final distortion in one go, then the source is said to be success ...

2014

A path choice approach to activity modeling with a pedestrian case study

Michel Bierlaire, Antonin Danalet

In Switzerland, the largest railway stations are called RailCities by the Swiss Railways. It emphasizes their transformation into places to perform different activities, similar to a small-scale city. Concerns are similar than in urban areas: costs of new ...

2014

Battle of the Water Networks II

Qi Wang, José Pedro Gamito de Saldanha Calado Matos, Marco Franchini

The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II pr ...

American Society of Civil Engineers2014

Adjustment of combination weights over adaptive diffusion networks

Ali H. Sayed

We show how the convergence time of an adaptive network can be estimated in a distributed manner by the agents. Using this procedure, we propose a distributed mechanism for the nodes to switch from using fixed doubly-stochastic combination weights to adapt ...

IEEE2014

Sparse Binary Features for Image Classification

Johann Paratte

In this work a new method for automatic image classification is proposed. It relies on a compact representation of images using sets of sparse binary features. This work first evaluates the Fast Retina Keypoint binary descriptor and proposes imp ...

2013

High-Dimensional Gaussian Process Bandits

Volkan Cevher, Andreas Krause

Many applications in machine learning require optimizing unknown functions defined over a high-dimensional space from noisy samples that are expensive to obtain. We address this notoriously hard challenge, under the assumptions that the function varies onl ...

2013

Accurate and efficient evaluation of failure probability for partial different equations with random input data

Alfio Quarteroni, Peng Chen

Several computational challenges arise when evaluating the failure probability of a given system in the context of risk prediction or reliability analysis. When the dimension of the uncertainties becomes high, well established direct numerical methods can ...

Elsevier Science Sa2013

Energy-aware adaptive bi-Lipschitz embeddings

Volkan Cevher, Bubacarr Bah, Ali Sadeghian

We propose a dimensionality reducing matrix design based on training data with constraints on its Frobenius norm and number of rows. Our design criteria is aimed at preserving the distances between the data points in the dimensionality reduced space as muc ...

2013

Optimal Sampling Rates in Infinite-Dimensional Compressed Sensing

Martin Vetterli, Loïc Arnaud Baboulaz, Mitra Fatemi

The theory of compressed sensing studies the problem of recovering a high dimensional sparse vector from its projections onto lower dimensional subspaces. The recently introduced framework of infinite-dimensional compressed sensing [1], to some extent gene ...

2013