no code implementations • 27 Jun 2023 • Asif Imran, Tevfik Kosar, Jaroslaw Zola, Muhammed Fatih Bulut
Although automated batch refactoring techniques are known to significantly improve overall software quality and maintainability, their impact on resource utilization is not well studied.
1 code implementation • 31 Aug 2018 • Frank Schoeneman, Jaroslaw Zola
Non-linear spectral dimensionality reduction methods, such as Isomap, remain important technique for learning manifolds.
4 code implementations • 12 Apr 2018 • Subhadeep Karan, Matthew Eichhorn, Blake Hurlburt, Grant Iraci, Jaroslaw Zola
We propose scalable methods to execute counting queries in machine learning applications.
no code implementations • 19 Feb 2018 • Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola
Scientific and engineering processes deliver massive high-dimensional data sets that are generated as non-linear transformations of an initial state and few process parameters.
1 code implementation • 18 May 2017 • Subhadeep Karan, Jaroslaw Zola
In Machine Learning, the parent set identification problem is to find a set of random variables that best explain selected variable given the data and some predefined scoring function.
no code implementations • 13 Nov 2016 • Frank Schoeneman, Suchismit Mahapatra, Varun Chandola, Nils Napp, Jaroslaw Zola
In this paper, we argue that a stable manifold can be learned using only a fraction of the stream, and the remaining stream can be mapped to the manifold in a significantly less costly manner.
1 code implementation • 9 Aug 2016 • Subhadeep Karan, Jaroslaw Zola
The problem of exact structure learning is to find a network structure that is optimal under certain scoring criteria.