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» A Guided Monte Carlo Approach to Optimization Problems
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DAC
2006
ACM
16 years 5 months ago
Generation of yield-aware Pareto surfaces for hierarchical circuit design space exploration
Pareto surfaces in the performance space determine the range of feasible performance values for a circuit topology in a given technology. We present a non-dominated sorting based ...
Saurabh K. Tiwary, Pragati K. Tiwary, Rob A. Ruten...
LION
2010
Springer
190views Optimization» more  LION 2010»
15 years 8 months ago
Algorithm Selection as a Bandit Problem with Unbounded Losses
Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
Matteo Gagliolo, Jürgen Schmidhuber
149
Voted
TOG
2008
92views more  TOG 2008»
15 years 4 months ago
Optimizing cubature for efficient integration of subspace deformations
We propose an efficient scheme for evaluating nonlinear subspace forces (and Jacobians) associated with subspace deformations. The core problem we address is efficient integration...
Steven S. An, Theodore Kim, Doug L. James
NIPS
2001
15 years 5 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...
ISPD
2012
ACM
248views Hardware» more  ISPD 2012»
13 years 12 months ago
A fast estimation of SRAM failure rate using probability collectives
Importance sampling is a popular approach to estimate rare event failures of SRAM cells. We propose to improve importance sampling by probability collectives. First, we use “Kul...
Fang Gong, Sina Basir-Kazeruni, Lara Dolecek, Lei ...