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CEAS
2006
Springer
15 years 1 months ago
Learning at Low False Positive Rates
Most spam filters are configured for use at a very low falsepositive rate. Typically, the filters are trained with techniques that optimize accuracy or entropy, rather than perfor...
Wen-tau Yih, Joshua Goodman, Geoff Hulten
HICSS
2009
IEEE
147views Biometrics» more  HICSS 2009»
15 years 4 months ago
Determining a Firm's Optimal Outsourcing Rate: A Learning Model Perspective
We present a decision model of a firm’s optimal outsourcing rate as an extension of Cha et. al [1]’s previous work on the economic risk of knowledge loss and deskilling in the...
Hoon S. Cha, David E. Pingry, Matt E. Thatcher
FOCM
2006
97views more  FOCM 2006»
14 years 9 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
EVOW
2008
Springer
14 years 11 months ago
Learning Gaussian Graphical Models of Gene Networks with False Discovery Rate Control
In many cases what matters is not whether a false discovery is made or not but the expected proportion of false discoveries among all the discoveries made, i.e. the so-called false...
Jose M. Peña
NIPS
2001
14 years 11 months ago
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Gregory Z. Grudic, Lyle H. Ungar