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ICML
2010
IEEE
13 years 11 months ago
2010
IEEE
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
ICML
2010
IEEE
13 years 11 months ago
2010
IEEE
In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-differe...
ICML
2010
IEEE
13 years 11 months ago
2010
IEEE
We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
Many real-world datasets can be clustered along multiple dimensions. For example, text documents can be clustered not only by topic, but also by the author's gender or sentim...