In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Accelerating the learning curve of software maintainers working on systems with which they have little familiarity motivated this study. A working hypothesis was that automated me...
There is current interest in generalizing Bayesian networks by using dependencies which are more general than probabilistic conditional independence (CI). Contextual dependencies, ...
– This paper describes a new technique for extracting clock-level finite state machines(FSMs) from transistor netlists using symbolic simulation. The transistor netlist is prepr...
Manish Pandey, Alok Jain, Randal E. Bryant, Derek ...
- The objective of this paper is to provide an effective technique for accurate modeling of the external input sequences that affect the behavior of Finite State Machines (FSMs). B...