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AAAI
2011
14 years 6 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
JMLR
2012
13 years 9 months ago
Fast interior-point inference in high-dimensional sparse, penalized state-space models
We present an algorithm for fast posterior inference in penalized high-dimensional state-space models, suitable in the case where a few measurements are taken in each time step. W...
Eftychios A. Pnevmatikakis, Liam Paninski
APPROX
2007
Springer
104views Algorithms» more  APPROX 2007»
16 years 24 days ago
Worst-Case to Average-Case Reductions Revisited
Abstract. A fundamental goal of computational complexity (and foundations of cryptography) is to find a polynomial-time samplable distribution (e.g., the uniform distribution) and...
Dan Gutfreund, Amnon Ta-Shma
IEEEPACT
2006
IEEE
16 years 19 days ago
Complexity-based program phase analysis and classification
Modeling and analysis of program behavior are at the foundation of computer system design and optimization. As computer systems become more adaptive, their efficiency increasingly...
Chang-Burm Cho, Tao Li
SIGGRAPH
2000
ACM
15 years 11 months ago
As-rigid-as-possible shape interpolation
We present an object-space morphing technique that blends the interiors of given two- or three-dimensional shapes rather than their boundaries. The morph is rigid in the sense tha...
Marc Alexa, Daniel Cohen-Or, David Levin