@inproceedings{901a6c469ed34e329e627c8c1138ad59,
title = "A dictionary updating scheme incorporating words elimination into Quantized Kernel Least-Mean-Squares for changing environments",
abstract = "Learning under time-varying environment is a challenging task since one has to deal with the ever changing distribution of data. A common and yet effective solution is to learn the data online and keep up with any ongoing changes. The Quantized Kernel Least-Squares (QKLMS) is an effective tool for online dictionary learning where the network size is capped by the quantization dictionary size. However, due to the lack of a mechanism to eliminate outdated words, learning can become irrelevant over time. In this paper, a mechanism to remove irrelevant words in the dictionary is proposed for QKLMS. Our experimental results based on chaotic time sequence prediction validate the capability of the developed method for time-varying data adaptation.",
keywords = "Changing environment learning, Kernel learning machine, Online learning, Vector quantization",
author = "Lei Sun and Badong Chen and Shengyu Nan and Zhiping Lin and Toh, {Kar Ann}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Digital Signal Processing, DSP 2015 ; Conference date: 21-07-2015 Through 24-07-2015",
year = "2015",
month = sep,
day = "9",
doi = "10.1109/ICDSP.2015.7252009",
language = "English",
series = "International Conference on Digital Signal Processing, DSP",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "911--915",
booktitle = "2015 IEEE International Conference on Digital Signal Processing, DSP 2015",
address = "United States",
}