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» Machine Learning by Function Decomposition
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GLOBECOM
2009
IEEE
15 years 3 months ago
Exploring Simulated Annealing and Graphical Models for Optimization in Cognitive Wireless Networks
In this paper we discuss the design of optimization algorithms for cognitive wireless networks (CWNs). Maximizing the perceived network performance towards applications by selectin...
Elena Meshkova, Janne Riihijärvi, Andreas Ach...
ICMLA
2008
15 years 1 months ago
A Clustering Approach in Developing Prognostic Systems of Cancer Patients
Accurate prediction of survival rates of cancer patients is often key to stratify patients for prognosis and treatment. Survival prediction is often accomplished by the TNM system...
Dechang Chen, Kai Xing, Donald Henson, Li Sheng, A...
IJCAI
2007
15 years 1 months ago
Explanation-Based Feature Construction
Choosing good features to represent objects can be crucial to the success of supervised machine learning algorithms. Good high-level features are those that concentrate informatio...
Shiau Hong Lim, Li-Lun Wang, Gerald DeJong
AAAI
2006
15 years 1 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
14 years 12 months ago
Necessary and sufficient conditions for success of the nuclear norm heuristic for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi