3 citations · 4 across the 2 of their papers we have counts for
4 papers
Temporally-Biased Sampling Schemes for Online Model Management
Brian Hentschel, Peter J. Haas, Yuanyuan Tian
To maintain the accuracy of supervised learning models in the presence of evolving data streams, we provide temporally-biased sampling schemes that weight recent data most heavily,…
MotherNets: Rapid Deep Ensemble Learning
Abdul Wasay, Brian Hentschel, Yuze Liao +2
Ensembles of deep neural networks significantly improve generalization accuracy. However, training neural network ensembles requires a large amount of computational resources and t…
The Internals of the Data Calculator
Stratos Idreos, Kostas Zoumpatianos, Brian Hentschel +2
Data structures are critical in any data-driven scenario, but they are notoriously hard to design due to a massive design space and the dependence of performance on workload and ha…
Temporally-Biased Sampling for Online Model Management
Brian Hentschel, Peter J. Haas, Yuanyuan Tian
To maintain the accuracy of supervised learning models in the presence of evolving data streams, we provide temporally-biased sampling schemes that weight recent data most heavily,…