1605 search results - page 75 / 321 » Metric Learning to Rank |
CORR
2010
Springer
13 years 8 months ago
2010
Springer
Centrality is an important notion in network analysis and is used to measure the degree to which network structure contributes to the importance of a node in a network. While many...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discrimina...
ICML
2003
IEEE
14 years 10 months ago
2003
IEEE
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
JMLR
2010
13 years 4 months ago
2010
In this paper, we propose a novel adaptive step-size approach for policy gradient reinforcement learning. A new metric is defined for policy gradients that measures the effect of ...
EMNLP
2008
13 years 11 months ago
2008
This paper investigates two strategies for improving coreference resolution: (1) training separate models that specialize in particular types of mentions (e.g., pronouns versus pr...