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BMCBI
2010
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13 years 4 months ago
Active learning for human protein-protein interaction prediction
Background: Biological processes in cells are carried out by means of protein-protein interactions. Determining whether a pair of proteins interacts by wet-lab experiments is reso...
Thahir P. Mohamed, Jaime G. Carbonell, Madhavi Gan...
SIGIR
2010
ACM
13 years 4 months ago
SED: supervised experimental design and its application to text classification
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...
Yi Zhen, Dit-Yan Yeung
NIPS
2000
13 years 5 months ago
Active Learning for Parameter Estimation in Bayesian Networks
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Simon Tong, Daphne Koller
UAI
2004
13 years 5 months ago
A Bayesian Approach toward Active Learning for Collaborative Filtering
Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the perfo...
Rong Jin, Luo Si
UAI
2004
13 years 5 months ago
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Omid Madani, Daniel J. Lizotte, Russell Greiner
NIPS
2004
13 years 5 months ago
Analysis of a greedy active learning strategy
act out the core search problem of active learning schemes, to better understand the extent to which adaptive labeling can improve sample complexity. We give various upper and low...
Sanjoy Dasgupta
IJCAI
2001
13 years 5 months ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
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
ECIR
2003
Springer
13 years 5 months ago
Representative Sampling for Text Classification Using Support Vector Machines
In order to reduce human efforts, there has been increasing interest in applying active learning for training text classifiers. This paper describes a straightforward active learni...
Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi W...
IADIS
2004
13 years 6 months ago
ALPS: Bringing Active Inquiry into Active Problem Solving
The ALPS project (Active Learning in Problem Solving) is building and evaluating an educational technology that combines cognitive tutors with a novel interactive questioning envi...
Scott M. Stevens, Albert T. Corbett, Kenneth R. Ko...