Abstract--We consider the problem of recovering a lowrank matrix when some of its entries, whose locations are not known a priori, are corrupted by errors of arbitrarily large magn...
Arvind Ganesh, John Wright, Xiaodong Li, Emmanuel ...
Some distributed constraint optimization algorithms use a linear number of messages in the number of agents, but of exponential size. This is often the main limitation for their pr...
Existing profile-guided partial redundancy elimination (PRE) methods use speculation to enable the removal of partial redundancies along more frequently executed paths at the expe...
Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Som...
One of the standard basic steps in drawing hierarchical graphs is to invert some arcs of the given graph to make the graph acyclic. We discuss exact and parameterized algorithms fo...