For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
We present an effective optimization framework for general SQLlike map-reduce queries, which is based on a novel query algebra and uses a small number of higher-order physical ope...
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Temporal datasets, in which data evolves continuously, exist in a wide variety of applications, and identifying anomalous or outlying objects from temporal datasets is an importan...
We introduce tensor displays: a family of compressive light field displays comprising all architectures employing a stack of timemultiplexed, light-attenuating layers illuminated...
Gordon Wetzstein, Douglas Lanman, Matthew Hirsch, ...
—There is a growing interest in exploiting interference (rather than avoiding it) to increase network throughput. In particular, the so-called successive interference cancellatio...
Canming Jiang, Yi Shi, Y. Thomas Hou, Wenjing Lou,...
The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning a...
We provide a flexible shape control technique in this paper for the automatic resizing of apparel products. The automatic resizing function has become an essential part of the 3D...
Variable selection problems are typically addressed under a penalized optimization framework. Nonconvex penalties such as the minimax concave plus (MCP) and smoothly clipped absol...
Scheduling data processing workflows (dataflows) on the cloud is a very complex and challenging task. It is essentially an optimization problem, very similar to query optimizati...
Herald Kllapi, Eva Sitaridi, Manolis M. Tsangaris,...