演講者:李育杰 教授 (國立交通大學應用數學系,中研院資訊科技創新研究中心)
講題:Distributed Consensus Reduced Support Vector Machine
時間:05/14(二) 13:20
地點:南大校區推廣教育大樓9407教室
摘要:Nowadays, machine learning performs astonishingly in many
different fields. The more data we have, our machine learning
methods will show better results. However, in some cases, the
data owners may not want to or not allow to share the data they
have. On the other hand, we may encounter extremely large data
sets that even cannot be stored in a single machine. In order
to deal with these two problems, we propose the distributed
consensus reduced support vector machine (DCRSVM) for binary
classification. Image that we have a set of local working units
and one center master. The DCSVM allows the local working units
share the local models without sharing their own data.
Iteratively, by sharing and updating the local models, the center
master will generate a consensus final model. The performance of
the consensus model is approximately as good as the model trained
by using all local working units’ data together. Similarly,
training an extremely large dataset, we can divide the dataset
into many partitions and dispatch the partitions to many
computation units. Thus, our proposed method can satisfy the
requirement of no data sharing.