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» Learning from Multiple Sources of Inaccurate Data
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SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
13 years 11 months ago
Predictive Modeling with Heterogeneous Sources
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip ...
ICML
2010
IEEE
13 years 11 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
INFOCOM
1998
IEEE
14 years 2 months ago
Informed-Source Coding-on-Demand (ISCOD) over Broadcast Channels
We present the Informed-Source Coding-On-Demand (ISCOD) approach for efficiently supplying non-identical data from a central server to multiple caching clients through a broadcast ...
Yitzhak Birk, Tomer Kol
CVPR
2010
IEEE
14 years 6 months ago
Learning from Interpolated Images using Neural Networks for Digital Forensics
Interpolated images have data redundancy, and special correlation exists among neighboring pixels, which is a crucial clue in digital forensics. We design a neural network based f...
Yizhen Huang, Na Fan
JCDL
2006
ACM
161views Education» more  JCDL 2006»
14 years 3 months ago
Learning metadata from the evidence in an on-line citation matching scheme
Citation matching, or the automatic grouping of bibliographic references that refer to the same document, is a data management problem faced by automatic digital libraries for sci...
Isaac G. Councill, Huajing Li, Ziming Zhuang, Sand...