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09/08/2022
FADE: Enabling Large-Scale Federated Adversarial Training on Resource-Constrained Edge Devices
Adversarial Training (AT) has been proven to be an effective method of i...
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07/14/2022
NASRec: Weight Sharing Neural Architecture Search for Recommender Systems
The rise of deep neural networks provides an important driver in optimiz...
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08/13/2021
MTG: A Benchmarking Suite for Multilingual Text Generation
We introduce MTG, a new benchmark suite for training and evaluating mult...
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06/07/2021
Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure
Enabling out-of-distribution (OOD) detection for DNNs is critical for th...
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04/07/2021
Enhancing Scientific Papers Summarization with Citation Graph
Previous work for text summarization in scientific domain mainly focused...
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03/24/2021
FedGP: Correlation-Based Active Client Selection for Heterogeneous Federated Learning
Client-wise heterogeneity is one of the major issues that hinder effecti...
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12/08/2020
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
Graph-based semi-supervised node classification (GraphSSC) has wide appl...
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12/06/2018
Trained Rank Pruning for Efficient Deep Neural Networks
The performance of Deep Neural Networks (DNNs) keeps elevating in recent...
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05/21/2018
SmoothOut: Smoothing Out Sharp Minima for Generalization in Large-Batch Deep Learning
In distributed deep learning, a large batch size in Stochastic Gradient ...
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09/15/2017
