Pan Zhou

EnlightenGAN: Deep Light Enhancement without Paired Supervision

Deep learning-based methods have achieved remarkable success in image re...
06/17/2019 ∙ by Yifan Jiang, et al. ∙ 26 ∙ share

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Prototypical Contrastive Learning of Unsupervised Representations

This paper presents Prototypical Contrastive Learning (PCL), an unsuperv...
05/11/2020 ∙ by Junnan Li, et al. ∙ 10 ∙ share

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Spatio-temporal Edge Service Placement: A Bandit Learning Approach

Shared edge computing platforms deployed at the radio access network are...
10/07/2018 ∙ by Lixing Chen, et al. ∙ 4 ∙ share

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Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs

Crowd counting is a challenging task due to the large variations in crow...
08/07/2019 ∙ by Zhikang Zou, et al. ∙ 4 ∙ share

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Exact Recovery of Tensor Robust Principal Component Analysis under Linear Transforms

This work studies the Tensor Robust Principal Component Analysis (TRPCA)...
07/16/2019 ∙ by Canyi Lu, et al. ∙ 2 ∙ share

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A Survey of Model Compression and Acceleration for Deep Neural Networks

Deep convolutional neural networks (CNNs) have recently achieved great s...
10/23/2017 ∙ by Yu Cheng, et al. ∙ 0 ∙ share

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Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification

Person Re-Identification (person re-id) is a crucial task as its applica...
08/03/2017 ∙ by Shuangjie Xu, et al. ∙ 0 ∙ share

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The Landscape of Deep Learning Algorithms

This paper studies the landscape of empirical risk of deep neural networ...
05/19/2017 ∙ by Pan Zhou, et al. ∙ 0 ∙ share

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Understanding Deep Representations through Random Weights

We systematically study the deep representation of random weight CNN (co...
04/02/2017 ∙ by Yao Shu, et al. ∙ 0 ∙ share

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Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks

Mobile Edge Computing (MEC) pushes computing functionalities away from t...
01/17/2018 ∙ by Jie Xu, et al. ∙ 0 ∙ share

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Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond

State-of-the-art pedestrian detection models have achieved great success...
04/05/2018 ∙ by Xi Ouyang, et al. ∙ 0 ∙ share

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Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification

We tackle the problem of person re-identification in video setting in th...
07/16/2018 ∙ by Xinxing Su, et al. ∙ 0 ∙ share

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Understanding Generalization and Optimization Performance of Deep CNNs

This work aims to provide understandings on the remarkable success of de...
05/28/2018 ∙ by Pan Zhou, et al. ∙ 0 ∙ share

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SmartSeed: Smart Seed Generation for Efficient Fuzzing

Fuzzing is an automated application vulnerability detection method. For ...
07/07/2018 ∙ by Chenyang Lv, et al. ∙ 0 ∙ share

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Adaptive Fog Configuration for the Industrial Internet of Things

Industrial Fog computing deploys various industrial services, such as au...
06/20/2018 ∙ by Lixing Chen, et al. ∙ 0 ∙ share

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Bayesian CycleGAN via Marginalizing Latent Sampling

Recent techniques built on Generative Adversarial Networks (GANs) like C...
11/19/2018 ∙ by Haoran You, et al. ∙ 0 ∙ share

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De-Health: All Your Online Health Information Are Belong to Us

In this paper, we study the privacy of online health data. We present a ...
02/02/2019 ∙ by Shouling Ji, et al. ∙ 0 ∙ share

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FDI: Quantifying Feature-based Data Inferability

Motivated by many existing security and privacy applications, e.g., netw...
02/02/2019 ∙ by Shouling Ji, et al. ∙ 0 ∙ share

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A Stochastic Trust Region Method for Non-convex Minimization

We target the problem of finding a local minimum in non-convex finite-su...
03/04/2019 ∙ by Zebang Shen, et al. ∙ 0 ∙ share

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Exploring RNN-Transducer for Chinese Speech Recognition

End-to-end approaches have drawn much attention recently for significant...
11/13/2018 ∙ by Senmao Wang, et al. ∙ 0 ∙ share

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Modality Attention for End-to-End Audio-visual Speech Recognition

Audio-visual speech recognition (AVSR) system is thought to be one of th...
11/13/2018 ∙ by Pan Zhou, et al. ∙ 0 ∙ share

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An Online Attention-based Model for Speech Recognition

Attention-based end-to-end (E2E) speech recognition models such as Liste...
11/13/2018 ∙ by Ruchao Fan, et al. ∙ 0 ∙ share

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Gradient Scheduling with Global Momentum for Non-IID Data Distributed Asynchronous Training

Distributed asynchronous offline training has received widespread attent...
02/21/2019 ∙ by Chengjie Li, et al. ∙ 0 ∙ share

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MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation

We address the problem of semi-supervised video object segmentation (VOS...
04/17/2019 ∙ by Shuangjie Xu, et al. ∙ 0 ∙ share

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Enhanced 3D convolutional networks for crowd counting

Recently, convolutional neural networks (CNNs) are the leading defacto m...
08/12/2019 ∙ by Zhikang Zou, et al. ∙ 0 ∙ share

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Enhancing Neural Sequence Labeling with Position-Aware Self-Attention

Sequence labeling is a fundamental task in natural language processing a...
08/24/2019 ∙ by Wei Wei, et al. ∙ 0 ∙ share

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Tell-the-difference: Fine-grained Visual Descriptor via a Discriminating Referee

In this paper, we investigate a novel problem of telling the difference ...
10/14/2019 ∙ by Shuangjie Xu, et al. ∙ 0 ∙ share

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Improving Generalization of Transformer for Speech Recognition with Parallel Schedule Sampling and Relative Positional Embedding

Transformer showed promising results in many sequence to sequence transf...
11/01/2019 ∙ by Pan Zhou, et al. ∙ 0 ∙ share

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Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach

Peer-to-peer knowledge transfer in distributed environments has emerged ...
02/06/2020 ∙ by Zeyue Xue, et al. ∙ 0 ∙ share

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Dynamic Graph Correlation Learning for Disease Diagnosis with Incomplete Labels

Disease diagnosis on chest X-ray images is a challenging multi-label cla...
02/26/2020 ∙ by Daizong Liu, et al. ∙ 0 ∙ share

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Prophet: Proactive Candidate-Selection for Federated Learning by Predicting the Qualities of Training and Reporting Phases

Federated Learning (FL) is viewed as a promising technique for future di...
02/03/2020 ∙ by Huawei Huang, et al. ∙ 0 ∙ share

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Crowd Counting via Hierarchical Scale Recalibration Network

The task of crowd counting is extremely challenging due to complicated d...
03/07/2020 ∙ by Zhikang Zou, et al. ∙ 0 ∙ share

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Cocktail: Cost-efficient and Data Skew-aware Online In-Network Distributed Machine Learning for Intelligent 5G and Beyond

To facilitate the emerging applications in the 5G networks and beyond, m...
04/02/2020 ∙ by Lingjun Pu, et al. ∙ 0 ∙ share

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Pan Zhou

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