15 citations · 61 across the 20 of their papers we have counts for
7 papers · 1 filter
Learning Deep Representations from Clinical Data for Chronic Kidney Disease
Duc Thanh Anh Luong, Varun Chandola
We study the behavior of a Time-Aware Long Short-Term Memory Autoencoder, a state-of-the-art method, in the context of learning latent representations from irregularly sampled pati…
Query Log Compression for Workload Analytics
Ting Xie, Oliver Kennedy, Varun Chandola
Analyzing database access logs is a key part of performance tuning, intrusion detection, benchmark development, and many other database administration tasks. Unfortunately, it is c…
dynamicMF: A Matrix Factorization Approach to Monitor Resource Usage in High Performance Computing Systems
Niyazi Sorkunlu, Duc Thanh Anh Luong, Varun Chandola
High performance computing (HPC) facilities consist of a large number of interconnected computing units (or nodes) that execute highly complex scientific simulations to support sci…
Detecting Data Leakage from Databases on Android Apps with Concept Drift
Gokhan Kul, Shambhu Upadhyaya, Varun Chandola
Mobile databases are the statutory backbones of many applications on smartphones, and they store a lot of sensitive information. However, vulnerabilities in the operating system or…
Hospital Readmission Prediction - Applying Hierarchical Sparsity Norms for Interpretable Models
Jialiang Jiang, Sharon Hewner, Varun Chandola
Hospital readmissions have become one of the key measures of healthcare quality. Preventable readmissions have been identified as one of the primary targets for reducing costs and…
Learning Manifolds from Non-stationary Streaming Data
Suchismit Mahapatra, Varun Chandola
Streaming adaptations of manifold learning based dimensionality reduction methods, such as Isomap, are based on the assumption that a small initial batch of observations is enough…
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…