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TNN
2008
177views more  TNN 2008»
15 years 4 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
SG
2010
Springer
15 years 10 months ago
Articulate: A Semi-automated Model for Translating Natural Language Queries into Meaningful Visualizations
While many visualization tools exist that offer sophisticated functions for charting complex data, they still expect users to possess a high degree of expertise in wielding the to...
Yiwen Sun, Jason Leigh, Andrew E. Johnson, Sangyoo...
153
Voted
AFP
2008
Springer
245views Formal Methods» more  AFP 2008»
15 years 11 months ago
Self-adjusting Computation with Delta ML
Abstract. In self-adjusting computation, programs respond automatically and efficiently to modifications to their data by tracking the dynamic data dependences of the computation ...
Umut A. Acar, Ruy Ley-Wild
CRV
2009
IEEE
225views Robotics» more  CRV 2009»
15 years 11 months ago
3D Modeling from Multiple Views with Integrated Registration and Data Fusion
This paper presents an integrated modeling system capable of generating coloured three dimensional representations of a scene observed from multiple viewpoints. Emphasis is given ...
Alain Boyer, Phillip Curtis, Pierre Payeur
147
Voted
SAC
2006
ACM
15 years 11 months ago
Evaluation of rule-based modularization in model transformation languages illustrated with ATL
This paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. Two scenarios are shown in which the modular units are id...
Ivan Kurtev, Klaas van den Berg, Fréd&eacut...