: Dimensionality reduction methods (DRs) have commonly been used as a principled way to understand the high-dimensional data such as face images. In this paper, we propose a new un...
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
In this paper we present the application of generalized retiming for temporal property checking. Retiming is a structural transformation that relocates registers in a circuit-based...
We study the intrinsic difficulty of solving linear parabolic initial value problems numerically at a single point. We present a worst case analysis for deterministic as well as fo...
In this paper we address the problem of finding an object in a polygonal environment as quickly as possible on average, with a team of mobile robots that can sense the environment...
Alejandro Sarmiento, Rafael Murrieta-Cid, Seth Hut...