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» On learning with dissimilarity functions
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BLISS
2009
IEEE
14 years 11 months ago
Autonomous Physical Secret Functions and Clone-Resistant Identification
Self configuring VLSI technology architectures offer a new environment for creating novel security functions. Two such functions for physical security architectures are proposed t...
Wael Adi
IPM
2008
100views more  IPM 2008»
14 years 10 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
HIS
2007
14 years 11 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
COLT
2008
Springer
14 years 11 months ago
Almost Tight Upper Bound for Finding Fourier Coefficients of Bounded Pseudo- Boolean Functions
A pseudo-Boolean function is a real-valued function defined on {0, 1}n . A k-bounded function is a pseudo-Boolean function that can be expressed as a sum of subfunctions each of w...
Sung-Soon Choi, Kyomin Jung, Jeong Han Kim
KDD
2004
ACM
135views Data Mining» more  KDD 2004»
15 years 10 months ago
Discovering additive structure in black box functions
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Giles Hooker