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» A Minimax Method for Learning Functional Networks
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IJCNN
2007
IEEE
14 years 1 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
AMC
2005
117views more  AMC 2005»
13 years 7 months ago
Teleonomic entropy: measuring the phase-space of end-directed systems
We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm desi...
Alexander Pudmenzky
ICML
2008
IEEE
14 years 8 months ago
Large scale manifold transduction
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...
WWW
2009
ACM
14 years 8 months ago
Discovering the staring people from social networks
In this paper, we study a novel problem of staring people discovery from social networks, which is concerned with finding people who are not only authoritative but also sociable i...
Dewei Chen, Jie Tang, Juanzi Li, Lizhu Zhou
SDM
2012
SIAM
305views Data Mining» more  SDM 2012»
11 years 10 months ago
Learning Hierarchical Relationships among Partially Ordered Objects with Heterogeneous Attributes and Links
Objects linking with many other objects in an information network may imply various semantic relationships. Uncovering such knowledge is essential for role discovery, data cleanin...
Chi Wang, Jiawei Han, Qi Li, Xiang Li, Wen-Pin Lin...