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IJCAI
2003
15 years 6 months ago
Gaussian Process Models of Spatial Aggregation Algorithms
Multi-level spatial aggregates are important for data mining in a variety of scientific and engineering applications, from analysis of weather data (aggregating temperature and p...
Naren Ramakrishnan, Christopher Bailey-Kellogg
CORR
2010
Springer
34views Education» more  CORR 2010»
15 years 5 months ago
Statistical Modelling of ft to Process Parameters in 30 nm Gate Length Finfets
This paper investigates the effect of process variations on unity gain frequency (ft) in 30 nm gate length FinFET by performing extensive TCAD simulations. Six different geometric...
B. Lakshmi, R. Srinivasan
118
Voted
NIPS
2000
15 years 6 months ago
Sparse Representation for Gaussian Process Models
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
Lehel Csató, Manfred Opper
ANOR
2002
57views more  ANOR 2002»
15 years 4 months ago
Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing
Abstract: We define events so as to reduce the number of events and decision variables needed for modeling batchscheduling problems such as described in [Westenberger and Kallrath ...
Siqun Wang, Monique Guignard
KDD
2010
ACM
435views Data Mining» more  KDD 2010»
15 years 8 months ago
Topic models with power-law using Pitman-Yor process
One of the important approaches for Knowledge discovery and Data mining is to estimate unobserved variables because latent variables can indicate hidden and specific properties o...
Issei Sato, Hiroshi Nakagawa