Linguistic-style-aware Neural Networks for Fake News Detection

1 code implementation • 7 Jan 2023 • Xinyi Zhou, Jiayu Li, Qinzhou Li, Reza Zafarani

We propose the hierarchical recursive neural network (HERO) to predict fake news by learning its linguistic style, which is distinguishable from the truth, as psychological theories reveal.

Fake News Detection

CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation

no code implementations • 4 Dec 2022 • Yirong Zhou, Chen Qian, Jiayu Li, Zi Wang, Yu Hu, Biao Qu, Liuhong Zhu, Jianjun Zhou, Taishan Kang, Jianzhong Lin, Qing Hong, Jiyang Dong, Di Guo, Xiaobo Qu

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI).

MRI Reconstruction

Rank Position Forecasting in Car Racing

no code implementations • 4 Oct 2020 • Bo Peng, Jiayu Li, Selahattin Akkas, Fugang Wang, Takuya Araki, Ohno Yoshiyuki, Judy Qiu

Forecasting is challenging since uncertainty resulted from exogenous factors exists.

Car Racing Model Optimization

Secure Multigroup Multicast Communication Systems via Intelligent Reflecting Surface

no code implementations • 17 Aug 2020 • Weiping Shi, Jiayu Li, Guiyang Xia, Yuntian Wang, Xiaobo Zhou, Yonghui Zhang, Feng Shu

This paper considers a secure multigroup multicast multiple-input single-output (MISO) communication system aided by an intelligent reflecting surface (IRS).

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

1 code implementation • 31 Dec 2018 • Ao Ren, Tianyun Zhang, Shaokai Ye, Jiayu Li, Wenyao Xu, Xuehai Qian, Xue Lin, Yanzhi Wang

The first part of ADMM-NN is a systematic, joint framework of DNN weight pruning and quantization using ADMM.

Model Compression Quantization

A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM

no code implementations • 5 Nov 2018 • Shaokai Ye, Tianyun Zhang, Kaiqi Zhang, Jiayu Li, Jiaming Xie, Yun Liang, Sijia Liu, Xue Lin, Yanzhi Wang

Both DNN weight pruning and clustering/quantization, as well as their combinations, can be solved in a unified manner.

Model Compression Quantization

Progressive Weight Pruning of Deep Neural Networks using ADMM

no code implementations • ICLR 2019 • Shaokai Ye, Tianyun Zhang, Kaiqi Zhang, Jiayu Li, Kaidi Xu, Yunfei Yang, Fuxun Yu, Jian Tang, Makan Fardad, Sijia Liu, Xiang Chen, Xue Lin, Yanzhi Wang

Motivated by dynamic programming, the proposed method reaches extremely high pruning rate by using partial prunings with moderate pruning rates.

Edge-computing Model Compression

Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs

no code implementations • 28 Mar 2018 • Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang

For FPGA implementations on deep convolutional neural networks (DCNNs), we achieve at least 152X and 72X improvement in performance and energy efficiency, respectively using the SWM-based framework, compared with the baseline of IBM TrueNorth processor under same accuracy constraints using the data set of MNIST, SVHN, and CIFAR-10.

On the Universal Approximation Property and Equivalence of Stochastic Computing-based Neural Networks and Binary Neural Networks

no code implementations • 14 Mar 2018 • Yanzhi Wang, Zheng Zhan, Jiayu Li, Jian Tang, Bo Yuan, Liang Zhao, Wujie Wen, Siyue Wang, Xue Lin

Based on the universal approximation property, we further prove that SCNNs and BNNs exhibit the same energy complexity.