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Refereed

CS033 Machine Learning Methods for High-Dimensional and Complex Data

Fri, May 1, 9:50 AM - 11:20 AM Room Executive Ballroom CD Hyatt Regency Milwaukee

Shahryar KarimiChair

Data Science Applications

3 Presentations

Difficulty-Aware Multi-Teacher Knowledge Distillation with Online Training-Sample Routing for Image Classification

9:55 AM - 10:20 AM

Co-authors: Avinash Rajendra, Avinash Rajendra, Avinash Rajendra, Mohammad Rahman (University of Wisconsin-Milwaukee)

machine learning deep learning knowledge distillation computer vision image classification neural network

Weak-Signal Aware Learning via Weighted Elastic Net Post-Selection Shrinkage for High-Dimensional Transcriptomics

10:20 AM - 10:45 AM

Co-authors: Fode Tounkara (The Ohio State University), Fode Tounkara (The Ohio State University)

Weak-Signal Detection Weighted Elastic Net Post-Selection Shrinkage High-Dimensional Transcriptomics Predictive Modeling

Neural Vector Autoregressive Models for Dimension Reduction in Time Series

10:45 AM - 11:10 AM

Co-authors: H.M. Wiranthe Herath (Drake University), H.M. Wiranthe Herath (Drake University)

Dimension reduction Neural networks Semi-parametric models Multivariate time series

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