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ISMIS
2005
Springer
16 years 5 days ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni
SBIA
2004
Springer
16 years 1 days ago
Learning with Class Skews and Small Disjuncts
One of the main objectives of a Machine Learning – ML – system is to induce a classifier that minimizes classification errors. Two relevant topics in ML are the understanding...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...
CVPR
2010
IEEE
15 years 12 months ago
Visual Tracking via Weakly Supervised Learning from Multiple Imperfect Oracles
Long-term persistent tracking in ever-changing environments is a challenging task, which often requires addressing difficult object appearance update problems. To solve them, most...
Bineng Zhong, Hongxun Yao, Sheng Chen, Xiaotong Yu...
CHI
2000
ACM
15 years 11 months ago
Alice: lessons learned from building a 3D system for novices
We present lessons learned from developing Alice, a 3D graphics programming environment designed for undergraduates with no 3D graphics or programming experience. Alice is a Windo...
Matthew Conway, Steve Audia, Tommy Burnette, Denni...
NIPS
2004
15 years 8 months ago
Incremental Learning for Visual Tracking
Most existing tracking algorithms construct a representation of a target object prior to the tracking task starts, and utilize invariant features to handle appearance variation of...
Jongwoo Lim, David A. Ross, Ruei-Sung Lin, Ming-Hs...