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» Input Modeling Using Quantile Statistical Methods
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93
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ICSE
1998
IEEE-ACM
15 years 4 months ago
A Model of Noisy Software Engineering Data (Status Report)
other projects in the database. Software development data is highly variable, which often result,s in underlying trends being hidden. In order to address this problem, a method of ...
Roseanne Tesoriero, Marvin V. Zelkowitz
NIPS
2003
15 years 2 months ago
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
Recent work has examined the estimation of models of stimulus-driven neural activity in which some linear filtering process is followed by a nonlinear, probabilistic spiking stag...
Jonathan Pillow, Liam Paninski, Eero P. Simoncelli
112
Voted
AI
1998
Springer
15 years 12 days ago
Uncertainty Measures of Rough Set Prediction
The main statistics used in rough set data analysis, the approximation quality, is of limited value when there is a choice of competing models for predicting a decision variable. ...
Ivo Düntsch, Günther Gediga
119
Voted
CIKM
2008
Springer
15 years 2 months ago
Modeling hidden topics on document manifold
Topic modeling has been a key problem for document analysis. One of the canonical approaches for topic modeling is Probabilistic Latent Semantic Indexing, which maximizes the join...
Deng Cai, Qiaozhu Mei, Jiawei Han, Chengxiang Zhai
97
Voted
PLDI
2006
ACM
15 years 6 months ago
Combining type-based analysis and model checking for finding counterexamples against non-interference
Type systems for secure information flow are useful for efficiently checking that programs have secure information flow. They are, however, conservative, so that they often rej...
Hiroshi Unno, Naoki Kobayashi, Akinori Yonezawa