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» Learning from Highly Structured Data by Decomposition
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ISBI
2009
IEEE
15 years 5 months ago
Quantitative Comparison of Spot Detection Methods in Live-Cell Fluorescence Microscopy Imaging
In live-cell fluorescence microscopy imaging, quantitative analysis of biological image data generally involves the detection of many subresolution objects, appearing as diffract...
Ihor Smal, Marco Loog, Wiro J. Niessen, Erik H. W....
ICDM
2007
IEEE
276views Data Mining» more  ICDM 2007»
15 years 4 months ago
SOPS: Stock Prediction Using Web Sentiment
Recently, the web has rapidly emerged as a great source of financial information ranging from news articles to personal opinions. Data mining and analysis of such financial info...
Vivek Sehgal, Charles Song
NIPS
2003
14 years 11 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
15 years 10 months ago
Classification features for attack detection in collaborative recommender systems
Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in r...
Robin D. Burke, Bamshad Mobasher, Chad Williams, R...
83
Voted
MPC
1995
Springer
116views Mathematics» more  MPC 1995»
15 years 1 months ago
Computer-Aided Computing
PVS is a highly automated framework for speci cation and veri cation. We show how the language and deduction features of PVS can be used to formalize, mechanize, and apply some us...
Natarajan Shankar