Methodology for feedback variable selection for control of semiconductor manufacturing processes-part 1: analytical and simulation results

O.D. Patterson;  Xiaobin Dong; P.P. Khargonekar; V.N. Nair

doi:10.1109/tsm.2003.818984

Methodology for feedback variable selection for control of semiconductor manufacturing processes-part 1: analytical and simulation results

IEEE Transactions on Semiconductor Manufacturing ◽

10.1109/tsm.2003.818984 ◽

2003 ◽

Vol 16 (4) ◽

pp. 575-587 ◽

Cited By ~ 5

Author(s):

O.D. Patterson ◽

Xiaobin Dong ◽

P.P. Khargonekar ◽

V.N. Nair

Keyword(s):

Variable Selection ◽

Semiconductor Manufacturing ◽

Manufacturing Processes ◽

Simulation Results ◽

Selection For

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Methodology for feedback variable selection for control of semiconductor manufacturing processes-part 2: application to reactive ion etching

IEEE Transactions on Semiconductor Manufacturing ◽

10.1109/tsm.2003.818962 ◽

2003 ◽

Vol 16 (4) ◽

pp. 588-597 ◽

Cited By ~ 5

Author(s):

O.D. Patterson ◽

Xiaobin Dong ◽

P.P. Khargonekar ◽

V.N. Nair ◽

D.S. Grimard

Keyword(s):

Variable Selection ◽

Semiconductor Manufacturing ◽

Reactive Ion Etching ◽

Manufacturing Processes ◽

Ion Etching ◽

Selection For

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Methodology for real-time feedback variable selection for manufacturing process control: theoretical and simulation results

10.1117/12.324332 ◽

1998 ◽

Author(s):

Oliver D. Patterson ◽

Pramod P. Khargonekar

Keyword(s):

Process Control ◽

Variable Selection ◽

Real Time ◽

Manufacturing Process ◽

Manufacturing Process Control ◽

Simulation Results ◽

Selection For

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Strong Consistency of Variable Selection for Stationary Linear Stochastic Systems

2019 Chinese Control Conference (CCC) ◽

10.23919/chicc.2019.8866312 ◽

2019 ◽

Author(s):

ZHAO Wenxiao ◽

YIN G. George ◽

BAI Er-Wei

Keyword(s):

Variable Selection ◽

Strong Consistency ◽

Stochastic Systems ◽

Linear Stochastic Systems ◽

Selection For

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Variable selection for semiparametric random-effects conditional density models with longitudinal data

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2018.1554130 ◽

2018 ◽

Vol 49 (4) ◽

pp. 977-996

Author(s):

Xiaohui Yuan ◽

Yue Wang ◽

Tianqing Liu

Keyword(s):

Variable Selection ◽

Longitudinal Data ◽

Random Effects ◽

Conditional Density ◽

Selection For

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Fault Detection via Sparse Representation for Semiconductor Manufacturing Processes

IEEE Transactions on Semiconductor Manufacturing ◽

10.1109/tsm.2014.2302011 ◽

2014 ◽

Vol 27 (2) ◽

pp. 252-259 ◽

Cited By ~ 12

Author(s):

Likun Ren ◽

Weimin Lv

Keyword(s):

Fault Detection ◽

Sparse Representation ◽

Semiconductor Manufacturing ◽

Manufacturing Processes

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Robust communication-efficient distributed composite quantile regression and variable selection for massive data

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2021.107262 ◽

2021 ◽

pp. 107262

Author(s):

Kangning Wang ◽

Shaomin Li ◽

Benle Zhang

Keyword(s):

Variable Selection ◽

Quantile Regression ◽

Massive Data ◽

Composite Quantile Regression ◽

Selection For

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Machine Learning Approaches Optimizing Semiconductor Manufacturing Processes

2021 5th IEEE Electron Devices Technology & Manufacturing Conference (EDTM) ◽

10.1109/edtm50988.2021.9420955 ◽

2021 ◽

Author(s):

Tsuyoshi Moriya

Keyword(s):

Machine Learning ◽

Semiconductor Manufacturing ◽

Manufacturing Processes ◽

Learning Approaches

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Generalized additive model with embedded variable selection for bankruptcy prediction: Prediction versus interpretation

Cogent Economics & Finance ◽

10.1080/23322039.2019.1597956 ◽

2019 ◽

Vol 7 (1) ◽

pp. 1597956

Author(s):

Carlos Valencia ◽

Sergio Cabrales ◽

Laura Garcia ◽

Juan Ramirez ◽

Diego Calderona ◽

...

Keyword(s):

Variable Selection ◽

Generalized Additive Model ◽

Additive Model ◽

Bankruptcy Prediction ◽

Selection For

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Variable Selection for Mixed Data Clustering: Application in Human Population Genomics

Journal of Classification ◽

10.1007/s00357-018-9301-y ◽

2019 ◽

Vol 37 (1) ◽

pp. 124-142 ◽

Cited By ~ 1

Author(s):

Matthieu Marbac ◽

Mohammed Sedki ◽

Tienne Patin

Keyword(s):

Variable Selection ◽

Data Clustering ◽

Human Population ◽

Population Genomics ◽

Mixed Data ◽

Selection For

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Automatic variable selection for varying coefficient models with longitudinal data

Statistics & Probability Letters ◽

10.1016/j.spl.2016.07.012 ◽

2016 ◽

Vol 119 ◽

pp. 84-90 ◽

Cited By ~ 1

Author(s):

Ruiqin Tian ◽

Liugen Xue ◽

Dengke Xu

Keyword(s):

Variable Selection ◽

Longitudinal Data ◽

Varying Coefficient Models ◽

Varying Coefficient ◽

Selection For

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