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JMLR
2012
13 years 10 months ago
A metric learning perspective of SVM: on the relation of LMNN and SVM
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...
Huyen Do, Alexandros Kalousis, Jun Wang, Adam Wozn...
JMLR
2012
13 years 10 months ago
Learning Low-order Models for Enforcing High-order Statistics
Models such as pairwise conditional random fields (CRFs) are extremely popular in computer vision and various other machine learning disciplines. However, they have limited expre...
Patrick Pletscher, Pushmeet Kohli
185
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ICML
1995
IEEE
16 years 8 months ago
Learning to Make Rent-to-Buy Decisions with Systems Applications
In the single rent-to-buy decision problem, without a priori knowledge of the amount of time a resource will be used we need to decide when to buy the resource, given that we can ...
P. Krishnan, Philip M. Long, Jeffrey Scott Vitter
IBPRIA
2009
Springer
16 years 3 days ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...
SIAMDM
2010
117views more  SIAMDM 2010»
15 years 5 months ago
Design is as Easy as Optimization
We consider the class of max-min and min-max optimization problems subject to a global budget (or weight) constraint and we undertake a systematic algorithmic and complexitytheore...
Deeparnab Chakrabarty, Aranyak Mehta, Vijay V. Vaz...