no code implementations • 9 Feb 2018 • Ryan P. Adams, Jeffrey Pennington, Matthew J. Johnson, Jamie Smith, Yaniv Ovadia, Brian Patton, James Saunderson
However, naive eigenvalue estimation is computationally expensive even when the matrix can be represented; in many of these situations the matrix is so large as to only be available implicitly via products with vectors.
no code implementations • ICLR 2019 • Zelda Mariet, Yaniv Ovadia, Jasper Snoek
Determinantal Point Processes (DPPs) provide an elegant and versatile way to sample sets of items that balance the point-wise quality with the set-wise diversity of selected items.
2 code implementations • NeurIPS 2019 • Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D. Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek
Modern machine learning methods including deep learning have achieved great success in predictive accuracy for supervised learning tasks, but may still fall short in giving useful estimates of their predictive {\em uncertainty}.
1 code implementation • 16 Jul 2020 • Ari Seff, Yaniv Ovadia, Wenda Zhou, Ryan P. Adams
Parametric computer-aided design (CAD) is the dominant paradigm in mechanical engineering for physical design.