Cheng Li

Robustness Testing of Language Understanding in Dialog Systems

Dec 30, 2020
Jiexi Liu, Ryuichi Takanobu, Jiaxin Wen, Dazhen Wan, Weiran Nie, Hongyan Li, Cheng Li, Wei Peng, Minlie Huang

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AIDE: Annotation-efficient deep learning for automatic medical image segmentation

Dec 14, 2020
Cheng Li, Rongpin Wang, Zaiyi Liu, Meiyun Wang, Hongna Tan, Yaping Wu, Xinfeng Liu, Hui Sun, Rui Yang, Xin Liu, Ismail Ben Ayed, Hairong Zheng, Hanchuan Peng, Shanshan Wang

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Simultaneously-Collected Multimodal Lying Pose Dataset: Towards In-Bed Human Pose Monitoring under Adverse Vision Conditions

Aug 20, 2020
Shuangjun Liu, Xiaofei Huang, Nihang Fu, Cheng Li, Zhongnan Su, Sarah Ostadabbas

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A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint

Aug 06, 2020
Weijian Huang, Hao Yang, Xinfeng Liu, Cheng Li, Ian Zhang, Rongpin Wang, Hairong Zheng, Shanshan Wang

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Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Document Matching

Apr 26, 2020
Liu Yang, Mingyang Zhang, Cheng Li, Michael Bendersky, Marc Najork

* arXiv preprint version. 10 pages

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Downstream Model Design of Pre-trained Language Model for Relation Extraction Task

Apr 08, 2020
Cheng Li, Ye Tian

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Incorporating Expert Prior in Bayesian Optimisation via Space Warping

Mar 27, 2020
Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh

* Knowledge-Based Systems (2020) 105663
* 21 Pages, 8 figures. To be published in Elsevier

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DLSpec: A Deep Learning Task Exchange Specification

Feb 26, 2020
Abdul Dakkak, Cheng Li, Jinjun Xiong, Wen-Mei Hwu

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Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling

Feb 26, 2020
Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Antonio Robles-Kelly, Svetha Venkatesh

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MLModelScope: A Distributed Platform for Model Evaluation and Benchmarking at Scale

Feb 19, 2020
Abdul Dakkak, Cheng Li, Jinjun Xiong, Wen-mei Hwu

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Non-rigid Registration Method between 3D CT Liver Data and 2D Ultrasonic Images based on Demons Model

Dec 31, 2019
Shuo Huang, Ke wu, Xiaolin Meng, Cheng Li

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DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs

Nov 20, 2019
Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu

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The Design and Implementation of a Scalable DL Benchmarking Platform

Nov 19, 2019
Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu

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Benanza: Automatic $μ$Benchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

Nov 19, 2019
Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu

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DLBricks: Composable Benchmark Generation toReduce Deep Learning Benchmarking Effort on CPUs

Nov 18, 2019
Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu

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Benanza: Automatic uBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

Nov 16, 2019
Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu

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Self-Adaptive Network Pruning

Oct 20, 2019
Jinting Chen, Zhaocheng Zhu, Cheng Li, Yuming Zhao

* Published as a conference paper at ICONIP 2019
* 10 pages, 5 figures, conference

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Efficiently Embedding Dynamic Knowledge Graphs

Oct 15, 2019
Tianxing Wu, Arijit Khan, Huan Gao, Cheng Li

* 14 pages

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AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers

Sep 23, 2019
Wei Zhang, Wei Wei, Lingjie Xu, Lingling Jin, Cheng Li

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Bayesian Network Based Risk and Sensitivity Analysis for Production Process Stability Control

Sep 10, 2019
Wei Xie, Bo Wang, Cheng Li, Jared Auclair, Peter Baker

* 42 pages, 4 figures, under review, submitted to European Journal of Operational Research (EJOR)

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Delving Deep Into Hybrid Annotations for 3D Human Recovery in the Wild

Aug 20, 2019
Yu Rong, Ziwei Liu, Cheng Li, Kaidi Cao, Chen Change Loy

* To appear in ICCV 2019. Code and models are available at https://penincillin.github.io/dct_iccv2019

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Across-Stack Profiling and Characterization of Machine Learning Models on GPUs

Aug 19, 2019
Cheng Li, Abdul Dakkak, Jinjun Xiong, Wei Wei, Lingjie Xu, Wen-mei Hwu

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Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging

Aug 06, 2019
Yanxia Chen, Taohui Xiao, Cheng Li, Qiegen Liu, Shanshan Wang

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Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation

Aug 06, 2019
Cheng Li, Hui Sun, Zaiyi Liu, Meiyun Wang, Hairong Zheng, Shanshan Wang

* 9 pages, 5 figures

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One-shot Face Reenactment

Aug 05, 2019
Yunxuan Zhang, Siwei Zhang, Yue He, Cheng Li, Chen Change Loy, Ziwei Liu

* To appear in BMVC 2019 as a spotlight presentation. Code and models are available at: https://github.com/bj80heyue/One_Shot_Face_Reenactment

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Accelerating Experimental Design by Incorporating Experimenter Hunches

Jul 22, 2019
Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin, Teo Slezak, Murray Height, Mazher Mohammed, Ian Gibson

* IEEE International Conference on Data Mining (ICDM) 2018

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Cheng Li

Robustness Testing of Language Understanding in Dialog Systems

AIDE: Annotation-efficient deep learning for automatic medical image segmentation

Simultaneously-Collected Multimodal Lying Pose Dataset: Towards In-Bed Human Pose Monitoring under Adverse Vision Conditions

A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint

A Complex KBQA System using Multiple Reasoning Paths

Towards in-store multi-person tracking using head detection and track heatmaps

Hierarchically Fair Federated Learning

Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Document Matching

Downstream Model Design of Pre-trained Language Model for Relation Extraction Task

Incorporating Expert Prior in Bayesian Optimisation via Space Warping

DLSpec: A Deep Learning Task Exchange Specification

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling

MLModelScope: A Distributed Platform for Model Evaluation and Benchmarking at Scale

Non-rigid Registration Method between 3D CT Liver Data and 2D Ultrasonic Images based on Demons Model

DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs

The Design and Implementation of a Scalable DL Benchmarking Platform

Benanza: Automatic $μ$Benchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

DLBricks: Composable Benchmark Generation toReduce Deep Learning Benchmarking Effort on CPUs

Benanza: Automatic uBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

Self-Adaptive Network Pruning

Efficiently Embedding Dynamic Knowledge Graphs

AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers

Bayesian Network Based Risk and Sensitivity Analysis for Production Process Stability Control

Delving Deep Into Hybrid Annotations for 3D Human Recovery in the Wild

Across-Stack Profiling and Characterization of Machine Learning Models on GPUs

Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging

Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation

One-shot Face Reenactment

Accelerating Experimental Design by Incorporating Experimenter Hunches