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» Sampling Methods for Unsupervised Learning
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KI
2002
Springer
15 years 3 days ago
Advantages, Opportunities and Limits of Empirical Evaluations: Evaluating Adaptive Systems
While empirical evaluations are a common research method in some areas of Artificial Intelligence (AI), others still neglect this approach. This article outlines both the opportun...
Stephan Weibelzahl, Gerhard Weber
112
Voted
ICCV
2009
IEEE
16 years 5 months ago
Domain Adaptive Semantic Diffusion for Large Scale Context-Based Video Annotation
Learning to cope with domain change has been known as a challenging problem in many real-world applications. This paper proposes a novel and efficient approach, named domain ada...
Yu-Gang Jiang, Jun Wang, Shih-Fu Chang, Chong-Wah ...
114
Voted
CVPR
2008
IEEE
16 years 2 months ago
Precise detailed detection of faces and facial features
Face detection has advanced dramatically over the past three decades. Algorithms can now quite reliably detect faces in clutter in or near real time. However, much still needs to ...
Liya Ding, Aleix M. Martínez
124
Voted
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
16 years 1 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
121
Voted
NIPS
2008
15 years 1 months ago
Breaking Audio CAPTCHAs
CAPTCHAs are computer-generated tests that humans can pass but current computer systems cannot. CAPTCHAs provide a method for automatically distinguishing a human from a computer ...
Jennifer Tam, Jirí Simsa, Sean Hyde, Luis v...