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» Using a Non-prior Training Active Feature Model
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TIP
2010
155views more  TIP 2010»
15 years 2 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
ACL
2001
15 years 5 months ago
Using Machine Learning Techniques to Interpret WH-questions
We describe a set of supervised machine learning experiments centering on the construction of statistical models of WH-questions. These models, which are built from shallow lingui...
Ingrid Zuckerman, Eric Horvitz
PKDD
2010
Springer
162views Data Mining» more  PKDD 2010»
15 years 2 months ago
Expectation Propagation for Bayesian Multi-task Feature Selection
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
Daniel Hernández-Lobato, José Miguel...
ICCSA
2005
Springer
15 years 10 months ago
M of N Features vs. Intrusion Detection
In order to complement the incomplete training audit trails, model generalization is always utilized to infer more unknown knowledge for intrusion detection. Thus, it is important ...
Zhuowei Li, Amitabha Das
SDM
2010
SIAM
156views Data Mining» more  SDM 2010»
15 years 5 months ago
Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Alireza Vahdatpour, Majid Sarrafzadeh