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» The Complexity of Forecast Testing
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CORR
2011
Springer
213views Education» more  CORR 2011»
13 years 3 months ago
Adapting to Non-stationarity with Growing Expert Ensembles
Forecasting sequences by expert ensembles generally assumes stationary or near-stationary processes; however, in complex systems and many real-world applications, we are frequentl...
Cosma Rohilla Shalizi, Abigail Z. Jacobs, Aaron Cl...
KDD
2012
ACM
221views Data Mining» more  KDD 2012»
11 years 11 months ago
Fast mining and forecasting of complex time-stamped events
Given huge collections of time-evolving events such as web-click logs, which consist of multiple attributes (e.g., URL, userID, timestamp), how do we find patterns and trends? Ho...
Yasuko Matsubara, Yasushi Sakurai, Christos Falout...
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
14 years 9 months ago
Camouflaged fraud detection in domains with complex relationships
We describe a data mining system to detect frauds that are camouflaged to look like normal activities in domains with high number of known relationships. Examples include accounti...
Sankar Virdhagriswaran, Gordon Dakin
AAAI
2000
13 years 10 months ago
Memory-Based Forecasting for Weather Image Patterns
A novel method and a framework called Memory-Based Forecasting are proposed to forecast complex and timevarying natural patterns with the goal of supporting experts' decision...
Kazuhiro Otsuka, Tsutomu Horikoshi, Satoshi Suzuki...
IDA
2009
Springer
14 years 3 months ago
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences
Abstract. This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes techniques as a complementary step to the model....
Francisco Martínez-Álvarez, Alicia T...