1 code implementation • 5 Jun 2018 • Nate Veldt, David Gleich, Anthony Wirth, James Saunderson
We outline a new approach for solving optimization problems which enforce triangle inequalities on output variables.
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.
1 code implementation • 2 May 2017 • Hamza Fawzi, James Saunderson, Pablo A. Parrilo
As such, we introduce strategies for constructing semidefinite approximations that we expect will be useful, more generally, for studying the approximation power of functions with small semidefinite representations.
Optimization and Control
no code implementations • NeurIPS 2013 • Matthew Johnson, James Saunderson, Alan Willsky
Sampling inference methods are computationally difficult to scale for many models in part because global dependencies can reduce opportunities for parallel computation.