Yuan Xie

A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks

In recent years, plenty of metrics have been proposed to identify networ...
01/01/2020 ∙ by Zhaodong Chen, et al. ∙ 28 ∙ share

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Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization

Spiking neural network is an important family of models to emulate the b...
11/03/2019 ∙ by Lei Deng, et al. ∙ 18 ∙ share

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Meta Segmentation Network for Ultra-Resolution Medical Images

Despite recent progress on semantic segmentation, there still exist huge...
02/19/2020 ∙ by Tong Wu, et al. ∙ 14 ∙ share

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Exploring Adversarial Attack in Spiking Neural Networks with Spike-Compatible Gradient

Recently, backpropagation through time inspired learning algorithms are ...
01/01/2020 ∙ by Ling Liang, et al. ∙ 14 ∙ share

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Comparing SNNs and RNNs on Neuromorphic Vision Datasets: Similarities and Differences

Neuromorphic data, recording frameless spike events, have attracted cons...
05/02/2020 ∙ by Weihua He, et al. ∙ 11 ∙ share

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Novelty Detection via Non-Adversarial Generative Network

One-class novelty detection is the process of determining if a query exa...
02/03/2020 ∙ by Chengwei Chen, et al. ∙ 8 ∙ share

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NTIRE 2020 Challenge on Image Demoireing: Methods and Results

This paper reviews the Challenge on Image Demoireing that was part of th...
05/06/2020 ∙ by Shanxin Yuan, et al. ∙ 8 ∙ share

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SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

We present SmartExchange, an algorithm-hardware co-design framework to t...
05/07/2020 ∙ by Yang Zhao, et al. ∙ 6 ∙ share

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Facial Landmark Machines: A Backbone-Branches Architecture with Progressive Representation Learning

Facial landmark localization plays a critical role in face recognition a...
12/10/2018 ∙ by Lingbo Liu, et al. ∙ 4 ∙ share

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Bi-GANs-ST for Perceptual Image Super-resolution

Image quality measurement is a critical problem for image super-resoluti...
11/01/2018 ∙ by Xiaotong Luo, et al. ∙ 2 ∙ share

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Semi-Supervised Video Salient Object Detection Using Pseudo-Labels

Deep learning-based video salient object detection has recently achieved...
08/12/2019 ∙ by Pengxiang Yan, et al. ∙ 2 ∙ share

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A Real-Time and Energy-Efficient Implementation of Difference-of-Gaussian with Flexible Thin-Film Transistors

With many advantageous features, softness and better biocompatibility, f...
03/07/2016 ∙ by Nan Wu, et al. ∙ 0 ∙ share

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Effective Image Retrieval via Multilinear Multi-index Fusion

Multi-index fusion has demonstrated impressive performances in retrieval...
09/27/2017 ∙ by Zhizhong Zhang, et al. ∙ 0 ∙ share

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DLAU: A Scalable Deep Learning Accelerator Unit on FPGA

As the emerging field of machine learning, deep learning shows excellent...
05/23/2016 ∙ by Chao Wang, et al. ∙ 0 ∙ share

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Robust Kernelized Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization

Most recently, tensor-SVD is implemented on multi-view self-representati...
09/15/2017 ∙ by Yanyun Qu, et al. ∙ 0 ∙ share

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Joint Hierarchical Category Structure Learning and Large-Scale Image Classification

We investigate the scalable image classification problem with a large nu...
09/15/2017 ∙ by Yanyun Qu, et al. ∙ 0 ∙ share

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On Unifying Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization

In this paper, we address the multi-view subspace clustering problem. Ou...
10/23/2016 ∙ by Yuan Xie, et al. ∙ 0 ∙ share

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Weighted Schatten p-Norm Minimization for Image Denoising and Background Subtraction

Low rank matrix approximation (LRMA), which aims to recover the underlyi...
12/03/2015 ∙ by Yuan Xie, et al. ∙ 0 ∙ share

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A New Low-Rank Tensor Model for Video Completion

In this paper, we propose a new low-rank tensor model based on the circu...
09/07/2015 ∙ by Wenrui Hu, et al. ∙ 0 ∙ share

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Weighted Schatten p-Norm Minimization for Image Denoising with Local and Nonlocal Regularization

This paper presents a patch-wise low-rank based image denoising method w...
01/07/2015 ∙ by Yuan Xie, et al. ∙ 0 ∙ share

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Distortion-driven Turbulence Effect Removal using Variational Model

It remains a challenge to simultaneously remove geometric distortion and...
01/17/2014 ∙ by Yuan Xie, et al. ∙ 0 ∙ share

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Bridging the Gap Between Neural Networks and Neuromorphic Hardware with A Neural Network Compiler

Different from training common neural networks (NNs) for inference on ge...
11/15/2017 ∙ by Yu Ji, et al. ∙ 0 ∙ share

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L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks

Batch Normalization (BN) has been proven to be quite effective at accele...
02/27/2018 ∙ by Shuang Wu, et al. ∙ 0 ∙ share

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Weakly Supervised Salient Object Detection Using Image Labels

Deep learning based salient object detection has recently achieved great...
03/17/2018 ∙ by Guanbin Li, et al. ∙ 0 ∙ share

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PIRT: A Runtime Framework to Enable Energy-Efficient Real-Time Robotic Applications on Heterogeneous Architectures

Enabling full robotic workloads with diverse behaviors on mobile systems...
02/23/2018 ∙ by Liu Liu, et al. ∙ 0 ∙ share

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Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training

Exploiting sparsity enables hardware systems to run neural networks fast...
06/01/2018 ∙ by Maohua Zhu, et al. ∙ 0 ∙ share

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Crossbar-aware neural network pruning

Crossbar architecture based devices have been widely adopted in neural n...
07/25/2018 ∙ by Ling Liang, et al. ∙ 0 ∙ share

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Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy

When learning from a batch of logged bandit feedback, the discrepancy be...
08/01/2018 ∙ by Yuan Xie, et al. ∙ 0 ∙ share

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Deep Multi-View Clustering via Multiple Embedding

Exploring the information among multiple views usually leads to more pro...
08/19/2018 ∙ by Bingqian Lin, et al. ∙ 0 ∙ share

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Dynamic Sparse Graph for Efficient Deep Learning

We propose to execute deep neural networks (DNNs) with dynamic and spars...
10/01/2018 ∙ by Liu Liu, et al. ∙ 0 ∙ share

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Batch Normalization Sampling

Deep Neural Networks (DNNs) thrive in recent years in which Batch Normal...
10/25/2018 ∙ by Zhaodong Chen, et al. ∙ 0 ∙ share

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QGAN: Quantized Generative Adversarial Networks

The intensive computation and memory requirements of generative adversar...
01/24/2019 ∙ by Peiqi Wang, et al. ∙ 0 ∙ share

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FPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture

Neural Network (NN) accelerators with emerging ReRAM (resistive random a...
01/28/2019 ∙ by Yu Ji, et al. ∙ 0 ∙ share

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Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers

Deep neural network (DNN) quantization converting floating-point (FP) da...
09/05/2019 ∙ by Yukuan Yang, et al. ∙ 0 ∙ share

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DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks

The rapidly growing parameter volume of deep neural networks (DNNs) hind...
11/19/2019 ∙ by Ao Ren, et al. ∙ 0 ∙ share

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In-memory multiplication engine with SOT-MRAM based stochastic computing

Processing-in-memory (PIM) turns out to be a promising solution to break...
09/22/2018 ∙ by Xin Ma, et al. ∙ 0 ∙ share

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Memristor Hardware-Friendly Reinforcement Learning

Recently, significant progress has been made in solving sophisticated pr...
01/20/2020 ∙ by Nan Wu, et al. ∙ 0 ∙ share

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Acoustic anomaly detection via latent regularized gaussian mixture generative adversarial networks

Acoustic anomaly detection aims at distinguishing abnormal acoustic sign...
02/04/2020 ∙ by Chengwei Chen, et al. ∙ 0 ∙ share

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SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor

Besides local features, global information plays an essential role in se...
01/24/2020 ∙ by Jiachen Xu, et al. ∙ 0 ∙ share

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AccD: A Compiler-based Framework for Accelerating Distance-related Algorithms on CPU-FPGA Platforms

As a promising solution to boost the performance of distance-related alg...
08/26/2019 ∙ by Yuke Wang, et al. ∙ 0 ∙ share

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Anomaly Detection by Latent Regularized Dual Adversarial Networks

Anomaly detection is a fundamental problem in computer vision area with ...
02/05/2020 ∙ by Chengwei Chen, et al. ∙ 0 ∙ share

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HyGCN: A GCN Accelerator with Hybrid Architecture

In this work, we first characterize the hybrid execution patterns of GCN...
01/07/2020 ∙ by Mingyu Yan, et al. ∙ 0 ∙ share

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Characterizing and Understanding GCNs on GPU

Graph convolutional neural networks (GCNs) have achieved state-of-the-ar...
01/28/2020 ∙ by Mingyu Yan, et al. ∙ 0 ∙ share

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A Secure and Persistent Memory System for Non-volatile Memory

In the non-volatile memory, ensuring the security and correctness of per...
01/03/2019 ∙ by Pengfei Zuo, et al. ∙ 0 ∙ share

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Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints

As neural networks continue their reach into nearly every aspect of soft...
03/10/2019 ∙ by Xing Hu, et al. ∙ 0 ∙ share

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Poq: Projection-based Runtime Assertions for Debugging on a Quantum Computer

In this paper, we propose Poq, a runtime assertion scheme for debugging ...
11/28/2019 ∙ by Gushu Li, et al. ∙ 0 ∙ share

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Computation on Sparse Neural Networks: an Inspiration for Future Hardware

Neural network models are widely used in solving many challenging proble...
04/24/2020 ∙ by Fei Sun, et al. ∙ 0 ∙ share

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TIMELY: Pushing Data Movements and Interfaces in PIM Accelerators Towards Local and in Time Domain

Resistive-random-access-memory (ReRAM) based processing-in-memory (R^2PI...
05/03/2020 ∙ by Weitao Li, et al. ∙ 0 ∙ share

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GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs

As the emerging trend of the graph-based deep learning, Graph Neural Net...
06/11/2020 ∙ by Yuke Wang, et al. ∙ 0 ∙ share

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Yuan Xie

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