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» Maximizing the guessability of symbolic input
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CHI
2005
ACM
14 years 5 months ago
Maximizing the guessability of symbolic input
Guessability is essential for symbolic input, in which users enter gestures or keywords to indicate characters or commands, or rely on labels or icons to access features. We prese...
Jacob O. Wobbrock, Htet Htet Aung, Brandon Rothroc...
CHARME
2005
Springer
145views Hardware» more  CHARME 2005»
13 years 6 months ago
Maximal Input Reduction of Sequential Netlists via Synergistic Reparameterization and Localization Strategies
Abstract. Automatic formal verification techniques generally require exponential resources with respect to the number of primary inputs of a netlist. In this paper, we present sev...
Jason Baumgartner, Hari Mony
RTS
2008
119views more  RTS 2008»
13 years 4 months ago
Symbolic quality control for multimedia applications
We present a fine grain quality control method for multimedia applications. The method takes as input an application software composed of actions. The execution times of actions a...
Jacques Combaz, Jean-Claude Fernandez, Joseph Sifa...
ICC
2007
IEEE
117views Communications» more  ICC 2007»
13 years 11 months ago
On The Optimal Amount of Training for Peak-Power-Limited Rayleigh Fading Channels
— We consider the optimal amount of training for single-antenna Rayleigh flat fading channels with peak-powerlimited input. The receiver uses known training symbols to perform m...
Wei Mao, Xin Su, Ming Zhao 0001, Xibin Xu
PDCAT
2009
Springer
13 years 11 months ago
Balanced Dense Polynomial Multiplication on Multi-Cores
Abstract— In symbolic computation, polynomial multiplication is a fundamental operation akin to matrix multiplication in numerical computation. We present efficient implementati...
Marc Moreno Maza, Yuzhen Xie