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KDD
2008
ACM
159views Data Mining» more  KDD 2008»
16 years 5 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan
JMLR
2010
185views more  JMLR 2010»
15 years 6 days ago
Multiple Kernel Learning on the Limit Order Book
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...
Tristan Fletcher, Zakria Hussain, John Shawe-Taylo...
KDD
2005
ACM
147views Data Mining» more  KDD 2005»
15 years 11 months ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu
LCN
2005
IEEE
15 years 11 months ago
Effective Channel Time Analysis for Mobile Broadband Wireless Networks
— We describe an algorithm to estimate the future cell throughput of a multi-rate broadband wireless network based on previous measurements. The total throughput of a cell depend...
Dennis Pong, Tim Moors
ICML
1994
IEEE
15 years 9 months ago
Efficient Algorithms for Minimizing Cross Validation Error
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Andrew W. Moore, Mary S. Lee