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cs.LG2019
Online Heterogeneous Mixture Learning for Big Data
Kazuki Seshimo, Ota Akira, Nishio Daichi +1
We propose the online machine learning for big data analysis with heterogeneity. We performed an experiment to compare the accuracy of each iteration between batch one and online o…
cs.LG2019★ 2 cited
Random Projection in Neural Episodic Control
Daichi Nishio, Satoshi Yamane
End-to-end deep reinforcement learning has enabled agents to learn with little preprocessing by humans. However, it is still difficult to learn stably and efficiently because the l…