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11/09/2022
Cold Start Streaming Learning for Deep Networks
The ability to dynamically adapt neural networks to newly-available data...
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03/20/2022
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
Graph Convolutional Networks (GCNs) is the state-of-the-art method for l...
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12/07/2021
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery
We propose a novel, structured pruning algorithm for neural networks – t...
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07/31/2021
Provably Efficient Lottery Ticket Discovery
The lottery ticket hypothesis (LTH) claims that randomly-initialized, de...
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07/27/2021
Exceeding the Limits of Visual-Linguistic Multi-Task Learning
By leveraging large amounts of product data collected across hundreds of...
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07/02/2021
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training
We propose , a novel distributed training protocol for Residual Networks...
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02/20/2021
GIST: Distributed Training for Large-Scale Graph Convolutional Networks
The graph convolutional network (GCN) is a go-to solution for machine le...
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11/28/2019
Data Augmentation for Deep Transfer Learning
Current approaches to deep learning are beginning to rely heavily on tra...
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03/25/2019