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» A Framework for Exploring Optimization Properties
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IJHPCA
2008
131views more  IJHPCA 2008»
13 years 8 months ago
De Novo Ultrascale Atomistic Simulations On High-End Parallel Supercomputers
We present a de novo hierarchical simulation framework for first-principles based predictive simulations of materials and their validation on high-end parallel supercomputers and ...
Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, ...
SIGOPSE
2004
ACM
14 years 2 months ago
Trust but verify: accountability for network services
This paper promotes accountability as a central design goal for dependable networked systems. We define three properties for accountable systems that extend beyond the basic secu...
Aydan R. Yumerefendi, Jeffrey S. Chase
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
14 years 2 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
ICML
2010
IEEE
13 years 10 months ago
Inverse Optimal Control with Linearly-Solvable MDPs
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Dvijotham Krishnamurthy, Emanuel Todorov
PAMI
2011
13 years 3 months ago
Approximately Global Optimization for Robust Alignment of Generalized Shapes
—In this paper, we introduce a novel method to solve shape alignment problems. We use gray-scale “images” to represent source shapes, and propose a novel two-component Gaussi...
Hongsheng Li, Tian Shen, Xiaolei Huang