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IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 ICML 2019 Poster #20 Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang, Yasaman Khazaeni IBM


  1. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 ICML 2019 Poster #20 Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang, Yasaman Khazaeni IBM Research, MIT-IBM Watson AI Lab June 12th 1

  2. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 Federated Learning

  3. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 Model fusion perspective

  4. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 Probabilistic Federated Neural Matching

  5. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 Simulated heterogeneous Federated Learning on MNIST Client 1 Client 2

  6. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 Examples of first layer weights Neuron 12 Neuron 21 Neuron 49 Client 1 Neuron 7 Neuron 8 Neuron 36 Client 2

  7. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 PFNM discovers correspondences among weights Client 1 Client 2 Client 1 Client 2 Client 2 Client 1 Neuron 12 Neuron 8 Neuron 49 Neuron 7 Neuron 36 Neuron 21 Matched neuron 8 Matched neuron 33 Matched neuron 44 Matched neuron 58

  8. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 Summary PFNM is a method for combining pre-trained fully-connected neural networks: • Can combine NNs trained on heterogeneous data without access to data • Can be further improved with few communication rounds (if data is available) • Outperforms Distributed SGD and Federated Averaging Technical contributions: • Indian Buffet Process based model to govern correspondences between weights of local neural networks. Applicable to multilayer networks • BNP allows for adaptive learning of global NN size • Fast MAP inference using iterative Hungarian algorithm

  9. IBM Research, MIT-IBM Watson AI Lab PFNM , Poster #20 THANK YOU | Please come to poster #2 #20 9

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