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» Evaluating algorithms that learn from data streams
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COLING
2002
15 years 11 days ago
Learning Verb Argument Structure from Minimally Annotated Corpora
In this paper we investigate the task of automatically identifying the correct argument structure for a set of verbs. The argument structure of a verb allows us to predict the rel...
Anoop Sarkar, Woottiporn Tripasai
248
Voted
CVPR
2010
IEEE
15 years 5 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...
INFOCOM
2010
IEEE
14 years 11 months ago
Buffer Management for Aggregated Streaming Data with Packet Dependencies
Abstract—In many applications the traffic traversing the network has inter-packet dependencies due to application-level encoding schemes. For some applications, e.g., multimedia...
Gabriel Scalosub, Peter Marbach, Jörg Liebehe...
WWW
2006
ACM
16 years 1 months ago
Online mining of frequent query trees over XML data streams
In this paper, we proposed an online algorithm, called FQT-Stream (Frequent Query Trees of Streams), to mine the set of all frequent tree patterns over a continuous XML data strea...
Hua-Fu Li, Man-Kwan Shan, Suh-Yin Lee
94
Voted
JCP
2006
111views more  JCP 2006»
15 years 15 days ago
Mining Developing Trends of Dynamic Spatiotemporal Data Streams
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
Yu Meng, Margaret H. Dunham