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IJCNN
2000
IEEE
13 years 9 months ago
Incremental Active Learning with Bias Reduction
The problem of designing input signals for optimal generalization in supervised learning is called active learning. In many active learning methods devised so far, the bias of the...
Masashi Sugiyama, Hidemitsu Ogawa
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
13 years 9 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
SIGMOD
2010
ACM
213views Database» more  SIGMOD 2010»
13 years 9 months ago
On active learning of record matching packages
We consider the problem of learning a record matching package (classifier) in an active learning setting. In active learning, the learning algorithm picks the set of examples to ...
Arvind Arasu, Michaela Götz, Raghav Kaushik
HRI
2010
ACM
13 years 9 months ago
Transparent active learning for robots
—This research aims to enable robots to learn from human teachers. Motivated by human social learning, we believe that a transparent learning process can help guide the human tea...
Crystal Chao, Maya Cakmak, Andrea Lockerd Thomaz
PAKDD
2004
ACM
143views Data Mining» more  PAKDD 2004»
13 years 10 months ago
Compact Dual Ensembles for Active Learning
Generic ensemble methods can achieve excellent learning performance, but are not good candidates for active learning because of their different design purposes. We investigate how...
Amit Mandvikar, Huan Liu, Hiroshi Motoda
MM
2004
ACM
151views Multimedia» more  MM 2004»
13 years 10 months ago
Multimodal concept-dependent active learning for image retrieval
It has been established that active learning is effective for learning complex, subjective query concepts for image retrieval. However, active learning has been applied in a conc...
Kingshy Goh, Edward Y. Chang, Wei-Cheng Lai
ICML
2004
IEEE
13 years 10 months ago
Active learning using pre-clustering
The paper is concerned with two-class active learning. While the common approach for collecting data in active learning is to select samples close to the classification boundary,...
Hieu Tat Nguyen, Arnold W. M. Smeulders
SIGCSE
2005
ACM
108views Education» more  SIGCSE 2005»
13 years 10 months ago
Teaching and learning ethics in computer science: walking the walk
The author shares techniques used in a successful "Ethics and Professionalism" class at California State University, San Bernardino. The author describes active learning...
Richard J. Botting
SAC
2005
ACM
13 years 10 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
MM
2005
ACM
160views Multimedia» more  MM 2005»
13 years 10 months ago
Putting active learning into multimedia applications: dynamic definition and refinement of concept classifiers
The authors developed an extensible system for video exploitation that puts the user in control to better accommodate novel situations and source material. Visually dense displays...
Ming-yu Chen, Michael G. Christel, Alexander G. Ha...