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» On learning with dissimilarity functions
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ICML
2004
IEEE
14 years 2 months ago
Active learning of label ranking functions
The effort necessary to construct labeled sets of examples in a supervised learning scenario is often disregarded, though in many applications, it is a time-consuming and expensi...
Klaus Brinker
ICML
2009
IEEE
14 years 10 months ago
A simpler unified analysis of budget perceptrons
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Ilya Sutskever
CANDC
2002
ACM
13 years 9 months ago
A model for information technologies that can be creative
To contribute to HCI investigation and interface design that develops interactive systems for creative solutions, I attempt to formulate a model of the human capability to combine...
Johan F. Hoorn
ICML
2009
IEEE
14 years 10 months ago
Geometry-aware metric learning
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon
ICML
2007
IEEE
14 years 10 months ago
Constructing basis functions from directed graphs for value function approximation
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
Jeffrey Johns, Sridhar Mahadevan