The impact of learning algorithm optimization by means of parameter tuning is studied. To do this, two quality attributes, sensitivity and classification performance, are investig...
While known algorithms for sensitivity analysis and parameter tuning in probabilistic networks have a running time that is exponential in the size of the network, the exact comput...
Current methods for interpreting oligonucleotidebased SNP-detection microarrays, SNP chips, are based on statistics and require extensive parameter tuning as well as extremely hig...
Michael Molla, Jude W. Shavlik, Thomas Albert, Tod...
— In this paper, we introduce a modified Kalman filter that can perform robust, real-time outlier detection in the observations, without the need for parameter tuning. Robotic ...