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» Incremental Markov-Model Planning
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CCS
2005
ACM
14 years 28 days ago
Keyboard acoustic emanations revisited
We examine the problem of keyboard acoustic emanations. We present a novel attack taking as input a 10-minute sound recording of a user typing English text using a keyboard, and t...
Li Zhuang, Feng Zhou, J. D. Tygar
USS
2010
13 years 5 months ago
Acoustic Side-Channel Attacks on Printers
We examine the problem of acoustic emanations of printers. We present a novel attack that recovers what a dotmatrix printer processing English text is printing based on a record o...
Michael Backes, Markus Dürmuth, Sebastian Ger...
INTERSPEECH
2010
13 years 2 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
AAAI
2011
12 years 7 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
ICRA
2005
IEEE
135views Robotics» more  ICRA 2005»
14 years 1 months ago
Sampling-Based Motion Planning Using Predictive Models
— Robotic motion planning requires configuration space exploration. In high-dimensional configuration spaces, a complete exploration is computationally intractable. Practical m...
Brendan Burns, Oliver Brock