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» Evaluating algorithms that learn from data streams
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NAACL
2007
15 years 6 months ago
Data-Driven Graph Construction for Semi-Supervised Graph-Based Learning in NLP
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
Andrei Alexandrescu, Katrin Kirchhoff
ICCV
2009
IEEE
16 years 9 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
PR
2011
14 years 7 months ago
A survey of multilinear subspace learning for tensor data
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
GLOBECOM
2008
IEEE
15 years 4 months ago
Wavelet-Based Traffic Analysis for Identifying Video Streams over Broadband Networks
Network and service providers are rapidly deploying IPTV networks to deliver a wide variety of video content to subscribers. Some video content may be protected by copyright and/or...
Yali Liu, Canhui Ou, Zhi Li, Cherita L. Corbett, C...
127
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KDD
2007
ACM
132views Data Mining» more  KDD 2007»
16 years 5 months ago
LungCAD: a clinically approved, machine learning system for lung cancer detection
We present LungCAD, a computer aided diagnosis (CAD) system that employs a classification algorithm for detecting solid pulmonary nodules from CT thorax studies. We briefly descri...
R. Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salgan...