Search Results for author: Blaise Aguera y Arcas

Found 4 papers, 4 papers with code

UIBert: Learning Generic Multimodal Representations for UI Understanding

1 code implementation29 Jul 2021 Chongyang Bai, Xiaoxue Zang, Ying Xu, Srinivas Sunkara, Abhinav Rastogi, Jindong Chen, Blaise Aguera y Arcas

Our key intuition is that the heterogeneous features in a UI are self-aligned, i. e., the image and text features of UI components, are predictive of each other.

Meta-Learning Bidirectional Update Rules

1 code implementation10 Apr 2021 Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Andrew Jackson, Tom Madams, Blaise Aguera y Arcas

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 for gradients, with update rules derived from the chain rule.

Meta-Learning

Generative Models for Effective ML on Private, Decentralized Datasets

2 code implementations ICLR 2020 Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Aguera y Arcas

To improve real-world applications of machine learning, experienced modelers develop intuition about their datasets, their models, and how the two interact.

Federated Learning

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