We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting update both classifier param...
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
In this paper, we address the problem of power dissipation minimization in combinational circuits implemented using pass transistor logic (PTL). We transform the problem of power ...
We propose a video event analysis framework based on object segmentation and tracking, combined with a Hidden Semi-Markov Model (HSMM) that uses state occupancy duration modeling....
This paper presents an effective fuzzy long-term semantic learning method for relevance feedback-based image retrieval. The proposed system uses a statistical correlationbased met...