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» Approximate Temporal Aggregation
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73
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ISCAS
2006
IEEE
105views Hardware» more  ISCAS 2006»
15 years 6 months ago
Lossless multi-channel EEG compression
— This paper presents a method for losslessly compressing multi-channel electroencephalogram signals. The Karhunen-Loeve transform is used to exploit the inter-correlation among ...
Yodchanan Wongsawat, Soontorn Oraintara, T. Tanaka...
138
Voted
SIGMOD
2004
ACM
144views Database» more  SIGMOD 2004»
16 years 25 days ago
Diamond in the Rough: Finding Hierarchical Heavy Hitters in Multi-Dimensional Data
Data items archived in data warehouses or those that arrive online as streams typically have attributes which take values from multiple hierarchies (e.g., time and geographic loca...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
ICDM
2009
IEEE
202views Data Mining» more  ICDM 2009»
14 years 10 months ago
Link Prediction on Evolving Data Using Matrix and Tensor Factorizations
Abstract--The data in many disciplines such as social networks, web analysis, etc. is link-based, and the link structure can be exploited for many different data mining tasks. In t...
Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda
109
Voted
CORR
2010
Springer
152views Education» more  CORR 2010»
15 years 24 days ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
105
Voted
INFOCOM
2006
IEEE
15 years 6 months ago
Reverse Hashing for High-Speed Network Monitoring: Algorithms, Evaluation, and Applications
— A key function for network traffic monitoring and analysis is the ability to perform aggregate queries over multiple data streams. Change detection is an important primitive w...
Robert T. Schweller, Zhichun Li, Yan Chen, Yan Gao...