Publications related to Active Learning of Bayesian Probabilistic Movement Primitives

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Supporting Teacher Decision-Making Through Appropriate Feedback

Roland John Tormey, Sébastien Cuendet

The quality of teaching is significantly enhanced through feedback to teachers about their teaching. Whereas systems to show student learning exist, those showing the emotional state of the classroom do not. We argue that such systems could greatly improve ...

Springer2016

Active Learning of Self-concordant like Multi-index Functions

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

We study the problem of actively learning a multi-index function of the form f (x) = g_0 (A_0 x) from its point evaluations, where A_0 ∈ R_{k×d} with k ≪ d. We build on the assumptions and techniques of an existing approach based on low-rank matrix recover ...

2015

Automatic Hand Phantom Map Detection Methods

Christian Enz, Claudio Bruschini, Huaiqi Huang, Tao Li, Jörn Justiz

Many amputees have maps of referred sensation from their missing hand on their residual limb (phantom maps). This skin area can serve as a target for providing amputees with tactile sensory feedback. Providing tactile feedback on the phantom map can improv ...

2015

Introducing Geometry in Active Learning for Image Segmentation

Pascal Fua, Raphael Sznitman, Ksenia Konyushkova

We propose an Active Learning approach to training a segmentation classifier that exploits geometric priors to streamline the annotation process in 3D image volumes. To this end, we use these priors not only to select voxels most in need of annotation but ...

2015

SVM Active Learning Approach for Image Classification Using Spatial Information

Devis Tuia

In the last few years, active learning has been gaining growing interest in the remote sensing community in optimizing the process of training sample collection for supervised image classification. Current strategies formulate the active learning problem i ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Active learning for monitoring network optimization

Devis Tuia, Alexei Pozdnoukhov

This book provides an introduction to spatio-temporal design that contains a description of one or two basic settings (e.g., migration and biodiversity) that includes real data sets, data-generating mechanisms, and possible simulation scenarios. Furthermor ...

John Wiley & Sons2013

Learning User's Confidence for Active Learning

Devis Tuia

In this paper, we study the applicability of active learning (AL) in operative scenarios. More particularly, we consider the well-known contradiction between the AL heuristics, which rank the pixels according to their uncertainty, and the user's confidence ...

Ieee-Inst Electrical Electronics Engineers Inc2013

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

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

Active Learning of Bayesian Probabilistic Movement Primitives

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Combining UAV-imagery and machine learning for wildlife conservation

Supporting Teacher Decision-Making Through Appropriate Feedback

Active Learning of Self-concordant like Multi-index Functions

Automatic Hand Phantom Map Detection Methods

Introducing Geometry in Active Learning for Image Segmentation

SVM Active Learning Approach for Image Classification Using Spatial Information

Active learning for monitoring network optimization

Active Learning: Any Value for Classification of Remotely Sensed Data?

Learning User's Confidence for Active Learning

Active Learning of Multi-Index Function Models

Combining UAV-imagery and machine learning for wildlife conservation

Active learning for monitoring network optimization

Active Learning of Self-concordant like Multi-index Functions

Active Learning: Any Value for Classification of Remotely Sensed Data?

Supporting Teacher Decision-Making Through Appropriate Feedback

SVM Active Learning Approach for Image Classification Using Spatial Information

Learning User's Confidence for Active Learning

Active Learning of Multi-Index Function Models

Automatic Hand Phantom Map Detection Methods

Introducing Geometry in Active Learning for Image Segmentation