2 citations · 5 across the 4 of their papers we have counts for
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Adaptive Granularity in Tensors: A Quest for Interpretable Structure
Ravdeep Pasricha, Ekta Gujral, Evangelos E. Papalexakis
Data collected at very frequent intervals is usually extremely sparse and has no structure that is exploitable by modern tensor decomposition algorithms. Thus the utility of such t…
OCTen: Online Compression-based Tensor Decomposition
Ekta Gujral, Ravdeep Pasricha, Tianxiong Yang +1
Tensor decompositions are powerful tools for large data analytics as they jointly model multiple aspects of data into one framework and enable the discovery of the latent structure…
Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition
Ravdeep Pasricha, Ekta Gujral, Evangelos E. Papalexakis
Tensor decompositions are used in various data mining applications from social network to medical applications and are extremely useful in discovering latent structures or concepts…