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05/04/2023
Cuttlefish: Low-Rank Model Training without All the Tuning
Recent research has shown that training low-rank neural networks can eff...
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02/24/2022
BagPipe: Accelerating Deep Recommendation Model Training
Deep learning based recommendation models (DLRM) are widely used in seve...
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03/05/2021
Pufferfish: Communication-efficient Models At No Extra Cost
To mitigate communication overheads in distributed model training, sever...
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02/28/2021
On the Utility of Gradient Compression in Distributed Training Systems
Rapid growth in data sets and the scale of neural network architectures ...
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02/02/2021
AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning
With the rapid adoption of machine learning (ML), a number of domains no...
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10/29/2020
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification
Distributed model training suffers from communication bottlenecks due to...
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07/09/2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Due to its decentralized nature, Federated Learning (FL) lends itself to...
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05/27/2019
Scalable K-Medoids via True Error Bound and Familywise Bandits
K-Medoids(KM) is a standard clustering method, used extensively on semi-...
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12/05/2018
Graph based Question Answering System
In today's digital age in the dawning era of big data analytics it is no...
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11/08/2014