no code implementations • 4 May 2023 • Hamed Valizadegan, Miguel J. S. Martinho, Jon M. Jenkins, Douglas A. Caldwell, Joseph D. Twicken, Stephen T. Bryson
Most existing exoplanets are discovered using validation techniques rather than being confirmed by complementary observations.
no code implementations • 19 Nov 2021 • Hamed Valizadegan, Miguel Martinho, Laurent S. Wilkens, Jon M. Jenkins, Jeffrey Smith, Douglas A. Caldwell, Joseph D. Twicken, Pedro C. Gerum, Nikash Walia, Kaylie Hausknecht, Noa Y. Lubin, Stephen T. Bryson, Nikunj C. Oza
ExoMiner is a highly accurate, explainable, and robust classifier that 1) allows us to validate 301 new exoplanets from the MAST Kepler Archive and 2) is general enough to be applied across missions such as the on-going TESS mission.
no code implementations • 2 Sep 2013 • Eric Heim, Hamed Valizadegan, Milos Hauskrecht
In this work, we explore methods for aiding the process of learning a kernel with the help of auxiliary kernels built from more easily extractable information regarding the relationships among objects.
no code implementations • NeurIPS 2009 • Hamed Valizadegan, Rong Jin, Ruofei Zhang, Jianchang Mao
Learning to rank is a relatively new field of study, aiming to learn a ranking function from a set of training data with relevancy labels.