Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
— Many asset tracking applications demand long-lived, low-cost, and continuous monitoring of a large number of items, which has posed a significant challenge to today’s RFID d...
Yu Zhang, Gautam D. Bhanage, Wade Trappe, Yanyong ...
Online boosting is one of the most successful online learning algorithms in computer vision. While many challenging online learning problems are inherently multi-class, online boo...
Amir Saffari, Martin Godec, Thomas Pock, Christian...