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KDD
2008
ACM
165views Data Mining» more  KDD 2008»
16 years 6 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
KDD
2000
ACM
101views Data Mining» more  KDD 2000»
15 years 9 months ago
Incremental quantile estimation for massive tracking
Data--call records, internet packet headers, or other transaction records--are coming down a pipe at a ferocious rate, and we need to monitor statistics of the data. There is no r...
Fei Chen, Diane Lambert, José C. Pinheiro
ICCV
2009
IEEE
16 years 11 months ago
Patch based Within-Object Classification
Advances in object detection have made it possible to collect large databases of certain objects. In this paper we exploit these datasets for within-object classification. For e...
Jania Aghajanian, Jonathan Warrell, Simon J.D. Pri...
ICDE
2007
IEEE
161views Database» more  ICDE 2007»
16 years 7 months ago
Mining Colossal Frequent Patterns by Core Pattern Fusion
Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the exist...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, H...
ICDE
2006
IEEE
163views Database» more  ICDE 2006»
16 years 7 months ago
A Sampling-Based Approach to Optimizing Top-k Queries in Sensor Networks
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy, usually the most precious resource in battery-powered ...
Adam Silberstein, Carla Schlatter Ellis, Jun Yang ...