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NIPS
2004
15 years 5 months ago
Instance-Specific Bayesian Model Averaging for Classification
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
Shyam Visweswaran, Gregory F. Cooper
CMS
2010
207views Communications» more  CMS 2010»
15 years 4 months ago
Statistical Detection of Malicious PE-Executables for Fast Offline Analysis
While conventional malware detection approaches increasingly fail, modern heuristic strategies often perform dynamically, which is not possible in many applications due to related ...
Ronny Merkel, Tobias Hoppe, Christian Krätzer...
ICPR
2006
IEEE
16 years 5 months ago
Competitive Mixtures of Simple Neurons
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
Karthik Sridharan, Matthew J. Beal, Venu Govindara...
ACL
2006
15 years 5 months ago
Unsupervised Relation Disambiguation Using Spectral Clustering
This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
WWW
2009
ACM
16 years 4 months ago
Web-scale classification with naive bayes
Traditional Naive Bayes Classifier performs miserably on web-scale taxonomies. In this paper, we investigate the reasons behind such bad performance. We discover that the low perf...
Congle Zhang, Gui-Rong Xue, Yong Yu, Hongyuan Zha