Sciweavers

EMNLP
2009
13 years 2 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
JMLR
2006
140views more  JMLR 2006»
13 years 4 months ago
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
Masashi Sugiyama
ICASSP
2010
IEEE
13 years 4 months ago
Speech modeling based on committee-based active learning
We propose a committee-based active learning method for large vocabulary continuous speech recognition. In this approach, multiple recognizers are prepared beforehand, and the rec...
Yuzu Hamanaka, Koichi Shinoda, Sadaoki Furui, Tada...
AAAI
1997
13 years 5 months ago
Active Learning with Committees for Text Categorization
In many real-world domains, supervised learning requires a large number of training examples. In this paper, we describe an active learning method that uses a committee of learner...
Ray Liere, Prasad Tadepalli
IJCAI
2001
13 years 5 months ago
Active Learning for Class Probability Estimation and Ranking
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Maytal Saar-Tsechansky, Foster J. Provost
IJCNN
2000
IEEE
13 years 8 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
AIRS
2008
Springer
13 years 10 months ago
Active Learning for Online Spam Filtering
Spam filtering is defined as a task trying to label emails with spam or ham in an online situation. The online feature requires the spam filter has a strong timely generalization a...
Wuying Liu, Ting Wang
ICASSP
2008
IEEE
13 years 10 months ago
Improving Spoken Language Understanding with information retrieval and active learning methods
In the context of deployed spoken dialogue telecom services, we introduce a preprocessor called Fiction into the Spoken Language Understanding (SLU) component. It acts as an inter...
Isabelle Jars, Franck Panaget
ICML
2001
IEEE
14 years 5 months ago
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other popular techniques that instead aim to reduce versio...
Nicholas Roy, Andrew McCallum
ICIP
2004
IEEE
14 years 5 months ago
Multi-label SVM active learning for image classification
Image classification is an important task in computer vision. However, how to assign suitable labels to images is a subjective matter, especially when some images can be categoriz...
Xuchun Li, Lei Wang, Eric Sung