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» On Unbiased Linear Approximations
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ML
2002
ACM
135views Machine Learning» more  ML 2002»
14 years 9 months ago
Bayesian Treed Models
When simple parametric models such as linear regression fail to adequately approximate a relationship across an entire set of data, an alternative may be to consider a partition o...
Hugh A. Chipman, Edward I. George, Robert E. McCul...
ML
2002
ACM
143views Machine Learning» more  ML 2002»
14 years 9 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
MP
2002
101views more  MP 2002»
14 years 9 months ago
Componentwise fast convergence in the solution of full-rank systems of nonlinear equations
The asymptotic convergence of parameterized variants of Newton's method for the solution of nonlinear systems of equations is considered. The original system is perturbed by a...
Nicholas I. M. Gould, Dominique Orban, Annick Sart...
SIGMETRICS
2002
ACM
128views Hardware» more  SIGMETRICS 2002»
14 years 9 months ago
High-density model for server allocation and placement
It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server alloca...
Craig W. Cameron, Steven H. Low, David X. Wei
TIT
2002
99views more  TIT 2002»
14 years 9 months ago
Feedback strategies for white Gaussian interference networks
A white Gaussian interference network is a channel with transmitters and receivers where the received symbols are linear combinations of the transmitted symbols and white Gaussian ...
Gerhard Kramer