With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
This paper describes a compiler for stream programs that efficiently schedules computational kernels and stream memory operations, and allocates on-chip storage. Our compiler uses...
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
The challenge we address is to reason about projected resource usage within a hierarchical task execution framework in order to improve agent effectiveness. Specifically, we seek ...
Developing parallel applications is notoriously difficult, but is even more complex for desktop applications. The added difficulties are primarily because of their interactive nat...