Boosted Embeddings for Time Series

<p>Sankeerth Rao Karingula, ML Researcher at Palo Alto Networks, joins us today to talk about his work “Boosted Embeddings for Time Series Forecasting.”</p> <p><br /> <strong>Works Mentioned</strong><br /> <a href="https://arxiv.org/abs/2104.04781">Boosted Embeddings for Time Series Forecasting</a><br /> by Sankeerth Rao Karingula, Nandini Ramanan, Rasool Tahmasbi, Mehrnaz Amjadi, Deokwoo Jung, Ricky Si, Charanraj Thimmisetty, Luisa Polania Cabrera, Marjorie Sayer, Claudionor Nunes Coelho Jr</p> <p><a href= "https://www.linkedin.com/in/sankeerthrao/">https://www.linkedin.com/in/sankeerthrao/</a></p> <p><a href= "https://twitter.com/sankeerthrao3">https://twitter.com/sankeerthrao3</a> </p> <p><a href= "https://lod2021.icas.cc/">https://lod2021.icas.cc/</a> </p>

Guest

Sankeerth Rao Karingula: Sankeerth Rao Karingula is a ML Researcher in the Applied AI team at Palo Alto Networks and works on Machine Learning based techniques for time series analysis. Dr. Karingula obtained his PhD majoring in Machine Learning and Data Science from University of California San Diego (UC San Diego) and his Bachelors, Masters in Communication and Signal Processing, Electrical Engineering from Indian Institute of Technology Bombay (IIT Bombay).