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» On the Complexity of Function Learning
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NIPS
2003
13 years 11 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan
ICML
2004
IEEE
14 years 3 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
AAAI
2011
12 years 10 months ago
CCRank: Parallel Learning to Rank with Cooperative Coevolution
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
AAAI
2000
13 years 11 months ago
Self-Organization of Innate Face Preferences: Could Genetics Be Expressed through Learning?
Self-organizing models develop realistic cortical structures when given approximations of the visual environment as input, and are an effective way to model the development of fac...
James A. Bednar, Risto Miikkulainen
ICML
2002
IEEE
14 years 10 months ago
Learning from Scarce Experience
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Leonid Peshkin, Christian R. Shelton