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» Active Learning for Structure in Bayesian Networks
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ALT
2008
Springer
15 years 6 months ago
Optimally Learning Social Networks with Activations and Suppressions
In this paper we consider the problem of learning hidden independent cascade social networks using exact value injection queries. These queries involve activating and suppressing a...
Dana Angluin, James Aspnes, Lev Reyzin
EMNLP
2006
14 years 11 months ago
Competitive generative models with structure learning for NLP classification tasks
In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
Kristina Toutanova
FLAIRS
2004
14 years 11 months ago
Case-Based Bayesian Network Classifiers
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
Eugene Santos, Ahmed Huessin
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
15 years 10 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
130
Voted
PRIB
2010
Springer
192views Bioinformatics» more  PRIB 2010»
14 years 8 months ago
Structured Output Prediction of Anti-cancer Drug Activity
We present a structured output prediction approach for classifying potential anti-cancer drugs. Our QSAR model takes as input a description of a molecule and predicts the activity...
Hongyu Su, Markus Heinonen, Juho Rousu