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NIPS
2001
13 years 6 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
TCAD
2008
136views more  TCAD 2008»
13 years 5 months ago
A Geometric Programming-Based Worst Case Gate Sizing Method Incorporating Spatial Correlation
We present an efficient optimization scheme for gate sizing in the presence of process variations. Our method is a worst-case design scheme, but it reduces the pessimism involved i...
Jaskirat Singh, Zhi-Quan Luo, Sachin S. Sapatnekar
BMCBI
2007
143views more  BMCBI 2007»
13 years 5 months ago
An adaptive bin framework search method for a beta-sheet protein homopolymer model
Background: The problem of protein structure prediction consists of predicting the functional or native structure of a protein given its linear sequence of amino acids. This probl...
Alena Shmygelska, Holger H. Hoos
ICCAD
2009
IEEE
117views Hardware» more  ICCAD 2009»
13 years 3 months ago
Binning optimization based on SSTA for transparently-latched circuits
With increasing process variation, binning has become an important technique to improve the values of fabricated chips, especially in high performance microprocessors where transpa...
Min Gong, Hai Zhou, Jun Tao, Xuan Zeng
TVLSI
2008
176views more  TVLSI 2008»
13 years 5 months ago
A Fuzzy Optimization Approach for Variation Aware Power Minimization During Gate Sizing
Abstract--Technology scaling in the nanometer era has increased the transistor's susceptibility to process variations. The effects of such variations are having a huge impact ...
Venkataraman Mahalingam, N. Ranganathan, J. E. Har...