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NIPS
2007
14 years 11 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
IJON
2002
85views more  IJON 2002»
14 years 9 months ago
Learning statistically efficient features for speaker recognition
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Gil-Jin Jang, Te-Won Lee, Yung-Hwan Oh
TAMC
2009
Springer
15 years 4 months ago
The Extended Turing Model as Contextual Tool
Computability concerns information with a causal – typically algorithmic – structure. As such, it provides a schematic analysis of many naturally occurring situations. We look ...
S. Barry Cooper
CIKM
2011
Springer
13 years 9 months ago
LogSig: generating system events from raw textual logs
Modern computing systems generate large amounts of log data. System administrators or domain experts utilize the log data to understand and optimize system behaviors. Most system ...
Liang Tang, Tao Li, Chang-Shing Perng
POPL
2010
ACM
15 years 7 months ago
Higher-Order Multi-Parameter Tree Transducers and Recursion Schemes for Program Verification
We introduce higher-order, multi-parameter, tree transducers (HMTTs, for short), which are kinds of higher-order tree transducers that take input trees and output a (possibly infi...
Naoki Kobayashi, Naoshi Tabuchi, Hiroshi Unno