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» A Nonlinear Predictive State Representation
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2007
136views Robotics» more  RSS 2007»
13 years 9 months ago
The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
Ron Alterovitz, Thierry Siméon, Kenneth Y. ...
BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein
INTERNET
2008
150views more  INTERNET 2008»
13 years 7 months ago
RPC and REST: Dilemma, Disruption, and Displacement
straction and explained how the Representational State Transfer (REST) architectural style is one alternative that can yield a superior approach to building distributed systems. Be...
Steve Vinoski
RECOMB
2004
Springer
14 years 8 months ago
Modeling and Analysis of Heterogeneous Regulation in Biological Networks
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Irit Gat-Viks, Amos Tanay, Ron Shamir
FOIS
2008
13 years 9 months ago
On the Syntax and Semantics of Effect Axioms
Effect axioms constitute the cornerstone of formal theories of action in AI. They drive standard reasoning tasks, especially prediction. These tasks need not be coupled with actual...
Haythem O. Ismail