15 citations · 34 across the 8 of their papers we have counts for
9 papers
Predicting the Impact of Batch Refactoring Code Smells on Application Resource Consumption
Asif Imran, Tevfik Kosar, Jaroslaw Zola +1
Automated batch refactoring has become a de-facto mechanism to restructure software that may have significant design flaws negatively impacting the code quality and maintainability…
Solving All-Pairs Shortest-Paths Problem in Large Graphs Using Apache Spark
Frank Schoeneman, Jaroslaw Zola
Algorithms for computing All-Pairs Shortest-Paths (APSP) are critical building blocks underlying many practical applications. The standard sequential algorithms, such as Floyd-Wars…
Scalable Manifold Learning for Big Data with Apache Spark
Frank Schoeneman, Jaroslaw Zola
Non-linear spectral dimensionality reduction methods, such as Isomap, remain important technique for learning manifolds. However, due to computational complexity, exact manifold le…
Privacy Preserving Analytics on Distributed Medical Data
Marina Blanton, Ah Reum Kang, Subhadeep Karan +1
Objective: To enable privacy-preserving learning of high quality generative and discriminative machine learning models from distributed electronic health records. Methods and Resul…
Fast Counting in Machine Learning Applications
Subhadeep Karan, Matthew Eichhorn, Blake Hurlburt +2
We propose scalable methods to execute counting queries in machine learning applications. To achieve memory and computational efficiency, we abstract counting queries and their con…
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes
Frank Schoeneman, Varun Chandola, Nils Napp +2
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. Map…
Applications and Challenges of Real-time Mobile DNA Analysis
Steven Y. Ko, Lauren Sassoubre, Jaroslaw Zola
The DNA sequencing is the process of identifying the exact order of nucleotides within a given DNA molecule. The new portable and relatively inexpensive DNA sequencers, such as Oxf…
Scalable Exact Parent Sets Identification in Bayesian Networks Learning with Apache Spark
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 funct…
Error Metrics for Learning Reliable Manifolds from Streaming Data
Frank Schoeneman, Suchismit Mahapatra, Varun Chandola +2
Spectral dimensionality reduction is frequently used to identify low-dimensional structure in high-dimensional data. However, learning manifolds, especially from the streaming data…