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10/13/2022
JOIST: A Joint Speech and Text Streaming Model For ASR
We present JOIST, an algorithm to train a streaming, cascaded, encoder e...
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03/22/2022
Pseudo Label Is Better Than Human Label
State-of-the-art automatic speech recognition (ASR) systems are trained ...
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10/01/2021
Large-scale ASR Domain Adaptation using Self- and Semi-supervised Learning
Self- and semi-supervised learning methods have been actively investigat...
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10/01/2021
Incremental Layer-wise Self-Supervised Learning for Efficient Speech Domain Adaptation On Device
Streaming end-to-end speech recognition models have been widely applied ...
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06/15/2021
On Large-Cohort Training for Federated Learning
Federated learning methods typically learn a model by iteratively sampli...
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08/14/2020
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning
The privacy-preserving federated learning for vertically partitioned dat...
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08/13/2020
Training Faster with Compressed Gradient
Although the distributed machine learning methods show the potential for...
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04/11/2020
Exploit Where Optimizer Explores via Residuals
To train neural networks faster, many research efforts have been devoted...
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02/25/2020
Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training
The communication of gradients is costly for training deep neural networ...
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02/06/2020
Faster On-Device Training Using New Federated Momentum Algorithm
Mobile crowdsensing has gained significant attention in recent years and...
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02/04/2020
Large Batch Training Does Not Need Warmup
Training deep neural networks using a large batch size has shown promisi...
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12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
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10/09/2019
Straggler-Agnostic and Communication-Efficient Distributed Primal-Dual Algorithm for High-Dimensional Data Mining
Recently, reducing communication time between machines becomes the main ...
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09/14/2019
Ouroboros: On Accelerating Training of Transformer-Based Language Models
Language models are essential for natural language processing (NLP) task...
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09/05/2019
Diversely Stale Parameters for Efficient Training of CNNs
The backpropagation algorithm is the most popular algorithm training neu...
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02/16/2019
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
Proximal gradient method has been playing an important role to solve man...
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12/02/2018
Ego-Downward and Ambient Video based Person Location Association
Using an ego-centric camera to do localization and tracking is highly ne...
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07/12/2018
Training Neural Networks Using Features Replay
Training a neural network using backpropagation algorithm requires passi...
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04/27/2018