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Documentation Delete f Aug 1, 2018
src Update Jun 21, 2018

Online Deep Learning: Learning Deep Neural Networks on the Fly

An implementation of the Hedge Backpropagation(HBP) proposed in Online Deep Learning: Learning Deep Neural Networks on the Fly

  title     = {Online Deep Learning: Learning Deep Neural Networks on the Fly},
  author    = {Doyen Sahoo and Quang Pham and Jing Lu and Steven C. H. Hoi},
  booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on
               Artificial Intelligence, {IJCAI-18}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},             
  pages     = {2660--2666},
  year      = {2018},
  month     = {7},
  doi       = {10.24963/ijcai.2018/369},
  url       = {},

Link to publication

Requirements and Installation

  • Theano 0.8.2
  • Keras 1.2.1

To install HBP, you need to replace the Keras's keras/engine/ file with our modified this doesn't affect normal projects that don't use HBP. Note that as the current HBP implementation only supports Keras 1.


  • To run HBP on the sample Higgs dataset, first download the data:
wget -O data/higgs.mat
  • To train HBP, run:
cd src/hbp
python -c hb19.yaml
  • To train other baseline models, run:
cd src/baselines

Data sets

The data used in our experiments are available at

Train HBP on your own data

We provide a sample script in src/ to train HBP on a new dataset. Feel free to modify the code to suit your experiments.