Nolan Miller — accepted AI-conference papers

2023

Decentralized Learning With Multi-Headed Distillation

Andrey Zhmoginov, Mark Sandler, Nolan Miller, Gus Kristiansen, Max Vladymyrov

CVPR 2023poster

Decentralized learning with private data is a central problem in machine learning. We propose a novel distillation-based decentralized learning technique that allows multiple agents with private non-iid data to learn from each other, without having to share their data, weights or weight updates. Our…

Cited by 5 Source ↗PDF ↗Scholar ↗

2021

Meta-Learning Bidirectional Update Rules

Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson +1

ICML 2021spotlight

In this paper, we introduce a new type of generalized neural network where neurons and synapses maintain multiple states. We show that classical gradient-based backpropagation in neural networks can be seen as a special case of a two-state network where one state is used for activations and another…

Cited by 16 Source ↗PDF ↗code ↗Scholar ↗