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» Learning on the Test Data: Leveraging Unseen Features
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ICML
2010
IEEE
13 years 10 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
ARTMED
1999
92views more  ARTMED 1999»
13 years 8 months ago
Two-Stage Machine Learning model for guideline development
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....
DIMVA
2008
13 years 10 months ago
Learning and Classification of Malware Behavior
Malicious software in form of Internet worms, computer viruses, and Trojan horses poses a major threat to the security of networked systems. The diversity and amount of its variant...
Konrad Rieck, Thorsten Holz, Carsten Willems, Patr...
ICPR
2004
IEEE
14 years 10 months ago
Learning Sample Subspace with Application to Face Detection
In this paper, we present a novel maximum correlation sample subspace method and apply it to human face detection [1] in still images. The algorithm starts by projecting all the t...
Guoping Qiu, Jianzhong Fang
ISMIS
2005
Springer
14 years 2 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni