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» When Can Formal Methods Make a Real Difference
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PKDD
2009
Springer
146views Data Mining» more  PKDD 2009»
15 years 8 months ago
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding prob...
Eva Besada-Portas, Sergey M. Plis, Jesús Ma...
113
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Graph-spectrum-based neural spike features for stereotrodes and tetrodes
Extracellular recording of neural signals records the action potentials (known as spikes) of neurons adjacent to the electrode as well as the noise generated by the overall neural...
Yasser Ghanbari, Panos Papamichalis, Larry Spence
128
Voted
COLING
2010
14 years 10 months ago
Automatic Temporal Expression Normalization with Reference Time Dynamic-Choosing
Temporal expressions in texts contain significant temporal information. Understanding temporal information is very useful in many NLP applications, such as information extraction,...
Xujian Zhao, Peiquan Jin, Lihua Yue
148
Voted
ICMLA
2010
15 years 1 months ago
Ensembles of Neural Networks for Robust Reinforcement Learning
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Alexander Hans, Steffen Udluft
124
Voted
ISSTA
2009
ACM
15 years 10 months ago
HAMPI: a solver for string constraints
Many automatic testing, analysis, and verification techniques for programs can be effectively reduced to a constraint-generation phase followed by a constraint-solving phase. Th...
Adam Kiezun, Vijay Ganesh, Philip J. Guo, Pieter H...