Sciweavers

COLT
2010
Springer
13 years 9 months ago
Active Learning on Trees and Graphs
We investigate the problem of active learning on a given tree whose nodes are assigned binary labels in an adversarial way. Inspired by recent results by Guillory and Bilmes, we c...
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio...
ICRA
2010
IEEE
148views Robotics» more  ICRA 2010»
13 years 9 months ago
Body schema acquisition through active learning
— We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using ...
Ruben Martinez-Cantin, Manuel Lopes, Luis Montesan...
PR
2007
205views more  PR 2007»
13 years 10 months ago
Active learning for image retrieval with Co-SVM
In relevance feedback algorithms, selective sampling is often used to reduce the cost of labeling and explore the unlabeled data. In this paper, we proposed an active learning alg...
Jian Cheng, Kongqiao Wang
ICML
2010
IEEE
14 years 7 days ago
Active Learning for Networked Data
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
Mustafa Bilgic, Lilyana Mihalkova, Lise Getoor
NIPS
2007
14 years 17 days ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
COLT
2005
Springer
14 years 4 months ago
Analysis of Perceptron-Based Active Learning
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
14 years 4 months ago
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
Thomas Takeo Osugi, Kun Deng, Stephen D. Scott
ICASSP
2009
IEEE
14 years 5 months ago
Maximizing global entropy reduction for active learning in speech recognition
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
ALT
2006
Springer
14 years 8 months ago
Active Learning in the Non-realizable Case
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
Matti Kääriäinen
SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
14 years 8 months ago
Spatially Cost-Sensitive Active Learning.
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Alexander Liu, Goo Jun, Joydeep Ghosh