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CORR
2007
Springer
167views Education» more  CORR 2007»
15 years 3 months ago
Optimal Solutions for Sparse Principal Component Analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
148
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NIPS
2001
15 years 4 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
123
Voted
AGENTS
1999
Springer
15 years 7 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
126
Voted
VLSID
1999
IEEE
97views VLSI» more  VLSID 1999»
15 years 7 months ago
A New Methodology for Concurrent Technology Development and Cell Library Optimization
To minimize the time to market and cost of new sub 0.25um process technologies and products, PDF Solutions, Inc., has developed a new comprehensive approach based on the use of pr...
Marko P. Chew, Sharad Saxena, Thomas F. Cobourn, P...
123
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PDPTA
2000
15 years 4 months ago
Performance Monitoring on an HPVM Cluster
Clusters of workstations are becoming popular platforms for parallel computing, but performance on these systems is more complex and harder to predict than on traditional parallel...
Geetanjali Sampemane, Scott Pakin, Andrew A. Chien