Publications related to Lower Bounds on Active Learning for Graphical Model Selection

Constrained Binary Identification Problem

We consider the problem of building a binary decision tree, to locate an object within a set by way of the least number of membership queries. This problem is equivalent to the “20 questions game” of information theory and is closely related to lossless so ...

2013

High-throughput scanning electrochemical microscopy brushing of strongly tilted and curved surfaces

Hubert Girault, Andreas Stephan Lesch, Fernando Cortes Salazar, Dmitry Momotenko, Gunther Wittstock

The feasibility of high-throughput scanning electrochemical microscopy (SECM) of strongly tilted (tilt angles ≤4°) and curved substrates (diameter of curvature ≥9 cm) is demonstrated by brushing them with a soft linear array of carbon microelectrodes. This ...

Elsevier2013

Discovering single classes in remote sensing images with active learning

Devis Tuia

When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. More ...

2012

Active Learning of Multi-Index Function Models

Volkan Cevher, Hemant Tyagi

We consider the problem of actively learning \textit{multi-index} functions of the form

f(x) = g(Ax)= \sum_{i=1}^k g_i(a_i^Tx)

from point evaluations of

f

. We assume that the function

f

is defined on an

\ell_2

-ball in

\Real^d

,

g

is twice contin ...

2012

Resolution-Invariant Separable Arma Modeling Of Images

Michaël Unser, Aurélien Bourquard, Hagay Kirshner

We suggest a continuous-domain stochastic modeling of images that is invariant to spatial resolution. Specifically, we are proposing an estimator that is calibrated with respect to the sampling step, and that can potentially handle aliased data. Motivated ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Resolution-Invariant Separable ARMA Modeling of Images

Michaël Unser, Aurélien Bourquard, Hagay Kirshner

We suggest a continuous-domain stochastic modeling of images that is invariant to spatial resolution. Specifically, we are proposing an estimator that is calibrated with respect to the sampling step, and that can potentially handle aliased data. Motivated ...

IEEE2011

Choice set generation for iterated DTA simulations

Michel Bierlaire, Gunnar Flötteröd

We apply the Metropolis-Hastings algorithm to efficiently sample from arbitrary paths distributions in a general network. Paths can be generalized into all-day travel plans through, e.g., an appropriate network expansion. The Metropolis-Hastings algorithm ...

2011

Degree-constrained edge partitioning in graphs arising from discrete tomography

Dominique de Werra, Bernard Ries

Starting from the basic problem of reconstructing a 2-dimensional image given by its projections on two axes, one associates a model of edge coloring in a complete bipartite graph. The complexity of the case with k=3 colors is open. Variations and special ...

2009

Channel estimation by inference on Gaussian Markov random fields

Thomas Riedl

In this paper, we discuss a novel method for channel estimation. The approach is based on the idea of modeling the complex channel gains by a Markov random field. This graphical model is used to capture the statistical dependencies between consecutive taps ...

2009

The arcsine law as a universal aging scheme for trap models

Jiri Cerny

We give a general proof of aging for trap models using the arcsine law for stable subordinators. This proof is based on abstract conditions on the potential theory of the underlying graph and on the randomness of the trapping landscape. We apply this proof ...

2008

Lower Bounds on Active Learning for Graphical Model Selection

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Constrained Binary Identification Problem

High-throughput scanning electrochemical microscopy brushing of strongly tilted and curved surfaces

Discovering single classes in remote sensing images with active learning

Active Learning of Multi-Index Function Models

Resolution-Invariant Separable Arma Modeling Of Images

Resolution-Invariant Separable ARMA Modeling of Images

Choice set generation for iterated DTA simulations

Degree-constrained edge partitioning in graphs arising from discrete tomography

Channel estimation by inference on Gaussian Markov random fields

The arcsine law as a universal aging scheme for trap models

Constrained Binary Identification Problem

Discovering single classes in remote sensing images with active learning

Active Learning of Multi-Index Function Models

Resolution-Invariant Separable Arma Modeling Of Images

Degree-constrained edge partitioning in graphs arising from discrete tomography

Resolution-Invariant Separable ARMA Modeling of Images

Choice set generation for iterated DTA simulations

High-throughput scanning electrochemical microscopy brushing of strongly tilted and curved surfaces

Channel estimation by inference on Gaussian Markov random fields

The arcsine law as a universal aging scheme for trap models