Search Results for author: Zhen Li

Found 99 papers, 49 papers with code

6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement Learning

1 code implementation21 Apr 2022 Tianyu Cui, Gaopeng Gou, Gang Xiong, Chang Liu, Peipei Fu, Zhen Li

6GAN forces multiple generators to train with a multi-class discriminator and an alias detector to generate non-aliased active targets with different addressing pattern types.

Decision Making reinforcement-learning

CLMLF:A Contrastive Learning and Multi-Layer Fusion Method for Multimodal Sentiment Detection

1 code implementation12 Apr 2022 Zhen Li, Bing Xu, Conghui Zhu, Tiejun Zhao

Compared with unimodal data, multimodal data can provide more features to help the model analyze the sentiment of data.

Contrastive Learning Sentiment Analysis

Towards An End-to-End Framework for Flow-Guided Video Inpainting

1 code implementation6 Apr 2022 Zhen Li, Cheng-Ze Lu, Jianhua Qin, Chun-Le Guo, Ming-Ming Cheng

Optical flow, which captures motion information across frames, is exploited in recent video inpainting methods through propagating pixels along its trajectories.

Optical Flow Estimation Video Inpainting

Graph Enhanced Contrastive Learning for Radiology Findings Summarization

1 code implementation ACL 2022 Jinpeng Hu, Zhuo Li, Zhihong Chen, Zhen Li, Xiang Wan, Tsung-Hui Chang

To address the limitation, we propose a unified framework for exploiting both extra knowledge and the original findings in an integrated way so that the critical information (i. e., key words and their relations) can be extracted in an appropriate way to facilitate impression generation.

Contrastive Learning

ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification

1 code implementation13 Feb 2022 Xinjie Lin, Gang Xiong, Gaopeng Gou, Zhen Li, Junzheng Shi, Jing Yu

In this paper, we propose a new traffic representation model called Encrypted Traffic Bidirectional Encoder Representations from Transformer (ET-BERT), which pre-trains deep contextualized datagram-level representation from large-scale unlabeled data.

Classification Traffic Classification

RoPGen: Towards Robust Code Authorship Attribution via Automatic Coding Style Transformation

1 code implementation12 Feb 2022 Zhen Li, Guenevere, Chen, Chen Chen, Yayi Zou, Shouhuai Xu

Recent studies show that current source code authorship attribution methods can be compromised by attackers exploiting adversarial examples and coding style manipulation.

Data Augmentation

HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks

2 code implementations20 Jan 2022 Su Zheng, Zhen Li, Yao Lu, Jingbo Gao, Jide Zhang, Lingli Wang

We propose an optimization method for the automatic design of approximate multipliers, which minimizes the average error according to the operand distributions.


Heuristic Search for Rank Aggregation with Application to Label Ranking

no code implementations11 Jan 2022 Yangming Zhou, Jin-Kao Hao, Zhen Li, Fred Glover

Rank aggregation aims to combine the preference rankings of a number of alternatives from different voters into a single consensus ranking.

CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization

no code implementations2 Dec 2021 Wei Liu, Huanqin Wu, Wenjing Mu, Zhen Li, Tao Chen, Dan Nie

We propose CO2Sum (Contrastive for Consistency), a contrastive learning scheme that can be easily applied on sequence-to-sequence models for factual-consistent abstractive summarization, proving that the model can be fact-aware without modifying the architecture.

Abstractive Text Summarization Contrastive Learning

Active Learning for Event Extraction with Memory-based Loss Prediction Model

no code implementations26 Nov 2021 Shirong Shen, Zhen Li, Guilin Qi

During the selection process, we use an internal-external sample loss ranking method to evaluate the sample importance by using local information.

Active Learning Event Extraction

Rapid Assessments of Light-Duty Gasoline Vehicle Emissions Using On-Road Remote Sensing and Machine Learning

no code implementations1 Oct 2021 Yan Xia, Linhui Jiang, Lu Wang, Xue Chen, Jianjie Ye, Tangyan Hou, Liqiang Wang, Yibo Zhang, Mengying Li, Zhen Li, Zhe Song, Yaping Jiang, Weiping Liu, Pengfei Li, Daniel Rosenfeld, John H. Seinfeld, Shaocai Yu

Our results show that the ORRS measurements, assisted by the machine-learning-based ensemble model developed here, can realize day-to-day supervision of on-road vehicle-specific emissions.

Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds

2 code implementations ICCV 2021 Chaoda Zheng, Xu Yan, Jiantao Gao, Weibing Zhao, Wei zhang, Zhen Li, Shuguang Cui

Current 3D single object tracking approaches track the target based on a feature comparison between the target template and the search area.

Frame Object Tracking

Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment

no code implementations5 Aug 2021 Qin Wang, Hui Che, Weizhen Ding, Li Xiang, Guanbin Li, Zhen Li, Shuguang Cui

Thus, we propose a novel framework based on a teacher-student architecture for the accurate colorectal polyp classification (CPC) through directly using white-light (WL) colonoscopy images in the examination.

Contrastive Learning

Shallow Feature Matters for Weakly Supervised Object Localization

1 code implementation CVPR 2021 Jun Wei, Qin Wang, Zhen Li, Sheng Wang, S. Kevin Zhou, Shuguang Cui

In practice, our SPOL model first generates the CAMs through a novel element-wise multiplication of shallow and deep feature maps, which filters the background noise and generates sharper boundaries robustly.

Weakly-Supervised Object Localization

Towards Making Deep Learning-based Vulnerability Detectors Robust

1 code implementation2 Aug 2021 Zhen Li, Jing Tang, Deqing Zou, Qian Chen, Shouhuai Xu, Chao Zhang, Yichen Li, Hai Jin

Automatically detecting software vulnerabilities in source code is an important problem that has attracted much attention.

Shallow Attention Network for Polyp Segmentation

1 code implementation2 Aug 2021 Jun Wei, Yiwen Hu, Ruimao Zhang, Zhen Li, S. Kevin Zhou, Shuguang Cui

To address the above issues, we propose the Shallow Attention Network (SANet) for polyp segmentation.

Video Polyp Segmentation

Inverse Problem of Nonlinear Schrödinger Equation as Learning of Convolutional Neural Network

no code implementations19 Jul 2021 Yiran Wang, Zhen Li

In this work, we use an explainable convolutional neural network (NLS-Net) to solve an inverse problem of the nonlinear Schr\"odinger equation, which is widely used in fiber-optic communications.

Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation

1 code implementation29 Jun 2021 Guangyi Liu, Zichao Yang, Tianhua Tao, Xiaodan Liang, Junwei Bao, Zhen Li, Xiaodong He, Shuguang Cui, Zhiting Hu

Such training objective is sub-optimal when the target sequence is not perfect, e. g., when the target sequence is corrupted with noises, or when only weak sequence supervision is available.

Machine Translation Style Transfer +3

Multi-Compound Transformer for Accurate Biomedical Image Segmentation

1 code implementation28 Jun 2021 Yuanfeng Ji, Ruimao Zhang, Huijie Wang, Zhen Li, Lingyun Wu, Shaoting Zhang, Ping Luo

The recent vision transformer(i. e. for image classification) learns non-local attentive interaction of different patch tokens.

Image Classification Semantic correspondence +1

An error analysis of generative adversarial networks for learning distributions

no code implementations27 May 2021 Jian Huang, Yuling Jiao, Zhen Li, Shiao Liu, Yang Wang, Yunfei Yang

This paper studies how well generative adversarial networks (GANs) learn probability distributions from finite samples.

CARLS: Cross-platform Asynchronous Representation Learning System

1 code implementation26 May 2021 Chun-Ta Lu, Yun Zeng, Da-Cheng Juan, Yicheng Fan, Zhe Li, Jan Dlabal, Yi-Ting Chen, Arjun Gopalan, Allan Heydon, Chun-Sung Ferng, Reah Miyara, Ariel Fuxman, Futang Peng, Zhen Li, Tom Duerig, Andrew Tomkins

In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge makers and knowledge banks -- to concertedly work together in an asynchronous fashion across hardware platforms.

Representation Learning

Combining Supervised and Un-supervised Learning for Automatic Citrus Segmentation

no code implementations4 May 2021 Heqing Huang, Tongbin Huang, Zhen Li, Zhiwei Wei, Shilei Lv

Compared with most of the existing citrus segmentation methods, our method uses a small amount of supervised data and a large number of unsupervised data, while learning the pixel level location information and the temporal information of citrus changes to enhance the segmentation effect.

Frame Semantic Segmentation

PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery

1 code implementation30 Apr 2021 Weibing Zhao, Xu Yan, Jiantao Gao, Ruimao Zhang, Jiayan Zhang, Zhen Li, Song Wu, Shuguang Cui

In this paper, we address a fundamental problem in PCSR: How to downsample the dense point cloud with arbitrary scales while preserving the local topology of discarding points in a case-agnostic manner (i. e. without additional storage for point relationship)?

Temporal Modulation Network for Controllable Space-Time Video Super-Resolution

1 code implementation CVPR 2021 Gang Xu, Jun Xu, Zhen Li, Liang Wang, Xing Sun, Ming-Ming Cheng

To well exploit the temporal information, we propose a Locally-temporal Feature Comparison (LFC) module, along with the Bi-directional Deformable ConvLSTM, to extract short-term and long-term motion cues in videos.

Frame Space-time Video Super-resolution +1

Free-form Description Guided 3D Visual Graph Network for Object Grounding in Point Cloud

1 code implementation ICCV 2021 Mingtao Feng, Zhen Li, Qi Li, Liang Zhang, Xiangdong Zhang, Guangming Zhu, HUI ZHANG, Yaonan Wang, Ajmal Mian

There are three main challenges in 3D object grounding: to find the main focus in the complex and diverse description; to understand the point cloud scene; and to locate the target object.

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

2 code implementations11 Feb 2021 Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, YunHsuan Sung, Zhen Li, Tom Duerig

In this paper, we leverage a noisy dataset of over one billion image alt-text pairs, obtained without expensive filtering or post-processing steps in the Conceptual Captions dataset.

 Ranked #1 on Image Classification on VTAB-1k (using extra training data)

Cross-Modal Retrieval Fine-Grained Image Classification +4

On the capacity of deep generative networks for approximating distributions

no code implementations29 Jan 2021 Yunfei Yang, Zhen Li, Yang Wang

Furthermore, it is shown that the approximation error in Wasserstein distance grows at most linearly on the ambient dimension and that the approximation order only depends on the intrinsic dimension of the target distribution.

GAKP: GRU Association and Kalman Prediction for Multiple Object Tracking

no code implementations28 Dec 2020 Zhen Li, Sunzeng Cai, Xiaoyi Wang, Zhe Liu, Nian Xue

Multiple Object Tracking (MOT) has been a useful yet challenging task in many real-world applications such as video surveillance, intelligent retail, and smart city.

Multiple Object Tracking

Operator learning for predicting multiscale bubble growth dynamics

no code implementations23 Dec 2020 Chensen Lin, Zhen Li, Lu Lu, Shengze Cai, Martin Maxey, George Em Karniadakis

Simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investigated systematically by deep neural networks (DNNs).

Computational Physics

Formal modeling and performance evaluation for hybrid systems:a probabilistic hybrid process algebra-based approach

no code implementations23 Dec 2020 Fujun Wang, Zining Cao, Lixing Tan, Zhen Li

After that, we present a performance evaluation language, CTRML, to reason over probabilistic systems, which extend the results to real number.

Formal Languages and Automata Theory F.4.3

Hierarchically nanostructured thermoelectric materials: Challenges and opportunities for improved power factors

no code implementations22 Dec 2020 Neophytos Neophytou, Vassilios Vargiamidis, Samuel Foster, Patrizio Graziosi, Laura de Sousa Oliveira, Dhritiman Chakraborty, Zhen Li, Mischa Thesberg, Hans Kosina, Nick Bennett, Giovanni Pennelli, Dario Narducci

Central to this ZT improvement is the drastic reduction in the material thermal conductivity due to the scattering of phonons on the numerous interfaces, boundaries, dislocations, point defects, phases, etc., which are purposely included.

Materials Science

Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion

1 code implementation7 Dec 2020 Xu Yan, Jiantao Gao, Jie Li, Ruimao Zhang, Zhen Li, Rui Huang, Shuguang Cui

In practice, an initial semantic segmentation (SS) of a single sweep point cloud can be achieved by any appealing network and then flows into the semantic scene completion (SSC) module as the input.

3D Semantic Scene Completion from a single RGB image Autonomous Driving +2

DeepSIM: GPS Spoofing Detection on UAVs using Satellite Imagery Matching

1 code implementation1 Dec 2020 Nian Xue, Liang Niu, Xianbin Hong, Zhen Li, Larissa Hoffaeller, Christina Pöpper

To detect GPS spoofing attacks, we investigate different deep neural network models that compare the real-time camera images with the historical satellite images.

SelfText Beyond Polygon: Unconstrained Text Detection with Box Supervision and Dynamic Self-Training

1 code implementation26 Nov 2020 Weijia Wu, Enze Xie, Ruimao Zhang, Wenhai Wang, Guan Pang, Zhen Li, Hong Zhou, Ping Luo

Although a polygon is a more accurate representation than an upright bounding box for text detection, the annotations of polygons are extremely expensive and challenging.

Delving Deep into Label Smoothing

2 code implementations25 Nov 2020 Chang-Bin Zhang, Peng-Tao Jiang, Qibin Hou, Yunchao Wei, Qi Han, Zhen Li, Ming-Ming Cheng

Experiments demonstrate that based on the same classification models, the proposed approach can effectively improve the classification performance on CIFAR-100, ImageNet, and fine-grained datasets.

Classification General Classification

Multi-Modal Active Learning for Automatic Liver Fibrosis Diagnosis based on Ultrasound Shear Wave Elastography

no code implementations2 Nov 2020 Lufei Gao, Ruisong Zhou, Changfeng Dong, Cheng Feng, Zhen Li, Xiang Wan, Li Liu

With the development of radiomics, noninvasive diagnosis like ultrasound (US) imaging plays a very important role in automatic liver fibrosis diagnosis (ALFD).

Active Learning

MedDG: A Large-scale Medical Consultation Dataset for Building Medical Dialogue System

1 code implementation15 Oct 2020 Wenge Liu, Jianheng Tang, Jinghui Qin, Lin Xu, Zhen Li, Xiaodan Liang

To push forward the future research on building expert-sensitive medical dialogue system, we proposes two kinds of medical dialogue tasks based on MedDG dataset.

Response Generation

UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation

no code implementations16 Sep 2020 Yuanfeng Ji, Ruimao Zhang, Zhen Li, Jiamin Ren, Shaoting Zhang, Ping Luo

Unlike the recent neural architecture search (NAS) methods that typically searched the optimal operators in each network layer, but missed a good strategy to search for feature aggregations, this paper proposes a novel NAS method for 3D medical image segmentation, named UXNet, which searches both the scale-wise feature aggregation strategies as well as the block-wise operators in the encoder-decoder network.

Neural Architecture Search Semantic Segmentation +1

Ultrasound Liver Fibrosis Diagnosis using Multi-indicator guided Deep Neural Networks

no code implementations10 Sep 2020 Jiali Liu, Wenxuan Wang, Tianyao Guan, Ningbo Zhao, Xiaoguang Han, Zhen Li

An indicator-guided learning mechanism is further proposed to ease the training of the proposed model.

Diagnosing Concept Drift with Visual Analytics

no code implementations28 Jul 2020 Weikai Yang, Zhen Li, Mengchen Liu, Yafeng Lu, Kelei Cao, Ross Maciejewski, Shixia Liu

Concept drift is a phenomenon in which the distribution of a data stream changes over time in unforeseen ways, causing prediction models built on historical data to become inaccurate.

Text Classification

IllumiNet: Transferring Illumination from Planar Surfaces to Virtual Objects in Augmented Reality

no code implementations12 Jul 2020 Di Xu, Zhen Li, Yanning Zhang, Qi Cao

This paper presents an illumination estimation method for virtual objects in real environment by learning.

Interactive Knowledge Distillation

no code implementations3 Jul 2020 Shipeng Fu, Zhen Li, Jun Xu, Ming-Ming Cheng, Zitao Liu, Xiaomin Yang

Knowledge distillation is a standard teacher-student learning framework to train a light-weight student network under the guidance of a well-trained large teacher network.

Knowledge Distillation

A Robust Attentional Framework for License Plate Recognition in the Wild

no code implementations6 Jun 2020 Linjiang Zhang, Peng Wang, Hui Li, Zhen Li, Chunhua Shen, Yanning Zhang

On the other hand, the 2D attentional based license plate recognizer with an Xception-based CNN encoder is capable of recognizing license plates with different patterns under various scenarios accurately and robustly.

Image Generation License Plate Recognition

Approximation in shift-invariant spaces with deep ReLU neural networks

no code implementations25 May 2020 Yunfei Yang, Zhen Li, Yang Wang

We also give lower bounds of the $L^p (1\le p \le \infty)$ approximation error for Sobolev spaces, which show that our construction of neural network is asymptotically optimal up to a logarithmic factor.

Exemplar Normalization for Learning Deep Representation

no code implementations CVPR 2020 Ruimao Zhang, Zhanglin Peng, Lingyun Wu, Zhen Li, Ping Luo

This work investigates a novel dynamic learning-to-normalize (L2N) problem by proposing Exemplar Normalization (EN), which is able to learn different normalization methods for different convolutional layers and image samples of a deep network.

Semantic Segmentation

PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling

1 code implementation CVPR 2020 Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, Shuguang Cui

Extensive experiments verify the robustness and superiority of our approach in point clouds processing tasks regardless of synthesis data, indoor data, and outdoor data with or without noise.

Automated classification of stems and leaves of potted plants based on point cloud data

no code implementations28 Feb 2020 Zichu Liu, Qing Zhang, Pei Wang, Zhen Li, Huiru Wang

A classification method was proposed to classify the leaves and stems of potted plants automatically based on the point cloud data of the plants, which is a nondestructive acquisition.

General Classification

BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation

no code implementations20 Jan 2020 Zhen-Liang Ni, Gui-Bin Bian, Guan-An Wang, Xiao-Hu Zhou, Zeng-Guang Hou, Xiao-Liang Xie, Zhen Li, Yu-Han Wang

For the scale variation, our adaptive receptive field module aggregates multi-scale features and automatically fuses them with different weights.

Semantic Segmentation

$μ$VulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection

no code implementations8 Jan 2020 Deqing Zou, Sujuan Wang, Shouhuai Xu, Zhen Li, Hai Jin

Existing vulnerability detection methods based on deep learning can detect the presence of vulnerabilities (i. e., addressing the binary classification or detection problem), but cannot pinpoint types of vulnerabilities (i. e., incapable of addressing multiclass classification).

General Classification Vulnerability Detection

Progressive Learning Algorithm for Efficient Person Re-Identification

no code implementations16 Dec 2019 Zhen Li, Hanyang Shao, Nian Xue, Liang Niu, Liangliang Cao

This paper studies the problem of Person Re-Identification (ReID)for large-scale applications.

Person Re-Identification

Attention-Guided Lightweight Network for Real-Time Segmentation of Robotic Surgical Instruments

1 code implementation24 Oct 2019 Zhen-Liang Ni, Gui-Bin Bian, Zeng-Guang Hou, Xiao-Hu Zhou, Xiao-Liang Xie, Zhen Li

LWANet adopts encoder-decoder architecture, where the encoder is the lightweight network MobileNetV2, and the decoder consists of depthwise separable convolution, attention fusion block, and transposed convolution.

PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs

no code implementations23 Sep 2019 Xuhui Meng, Zhen Li, Dongkun Zhang, George Em. Karniadakis

Consequently, compared to the original PINN approach, the proposed PPINN approach may achieve a significant speedup for long-time integration of PDEs, assuming that the CG solver is fast and can provide reasonable predictions of the solution, hence aiding the PPINN solution to converge in just a few iterations.

Small Data Image Classification

Semi-Supervised Video Salient Object Detection Using Pseudo-Labels

1 code implementation ICCV 2019 Pengxiang Yan, Guanbin Li, Yuan Xie, Zhen Li, Chuan Wang, Tianshui Chen, Liang Lin

Specifically, we present an effective video saliency detector that consists of a spatial refinement network and a spatiotemporal module.

 Ranked #1 on Video Salient Object Detection on VOS-T (using extra training data)

Salient Object Detection Unsupervised Video Object Segmentation +1

Convergence Rates of Posterior Distributions in Markov Decision Process

no code implementations22 Jul 2019 Zhen Li, Eric Laber

In this paper, we show the convergence rates of posterior distributions of the model dynamics in a MDP for both episodic and continuous tasks.

Gated Multiple Feedback Network for Image Super-Resolution

1 code implementation9 Jul 2019 Qilei Li, Zhen Li, Lu Lu, Gwanggil Jeon, Kai Liu, Xiaomin Yang

The rapid development of deep learning (DL) has driven single image super-resolution (SR) into a new era.

Image Super-Resolution

Influence of Boundaries and Thermostatting on Nonequilibrium Molecular Dynamics Simulations of Heat Conduction in Solids

no code implementations27 May 2019 Zhen Li, Shiyun Xiong, Charles Sievers, Yue Hu, Zheyong Fan, Ning Wei, Hua Bao, Shunda Chen, Davide Donadio, Tapio Ala-Nissila

Conventionally, the thermal conductivity of a finite system is calculated as the ratio between the heat flux and the temperature gradient extracted from the linear part of the temperature profile away from the local thermostats.

Mesoscale and Nanoscale Physics Statistical Mechanics Computational Physics

Efficient hinging hyperplanes neural network and its application in nonlinear system identification

no code implementations15 May 2019 Jun Xu, Qinghua Tao, Zhen Li, Xiangming Xi, Johan A. K. Suykens, Shuning Wang

It is proved that for every EHH neural network, there is an equivalent adaptive hinging hyperplanes (AHH) tree, which was also proposed based on the model of HH and find good applications in system identification.

Variable Selection

A GPU-accelerated package for simulation of flow in nanoporous source rocks with many-body dissipative particle dynamics

2 code implementations25 Mar 2019 Yidong Xia, Ansel Blumers, Zhen Li, Lixiang Luo, Yu-Hang Tang, Joshua Kane, Hai Huang, Matthew Andrew, Milind Deo, Jan Goral

Lastly, we demonstrate, through a flow simulation in realistic shale pores, that the CPU counterpart requires 840 Power9 cores to rival the performance delivered by our package with four V100 GPUs on ORNL's Summit architecture.

Computational Physics

Feedback Network for Image Super-Resolution

4 code implementations CVPR 2019 Zhen Li, Jinglei Yang, Zheng Liu, Xiaomin Yang, Gwanggil Jeon, Wei Wu

In this paper, we propose an image super-resolution feedback network (SRFBN) to refine low-level representations with high-level information.

Image Super-Resolution

Graph-RISE: Graph-Regularized Image Semantic Embedding

1 code implementation14 Feb 2019 Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng, Aleksei Timofeev, Yi-Ting Chen, Yaxi Gao, Tom Duerig, Andrew Tomkins, Sujith Ravi

Learning image representations to capture fine-grained semantics has been a challenging and important task enabling many applications such as image search and clustering.

General Classification Graph Learning +2

Thompson Sampling for Pursuit-Evasion Problems

no code implementations11 Nov 2018 Zhen Li, Nicholas J. Meyer, Eric B. Laber, Robert Brigantic

We propose a variant of Thompson Sampling for pursuit-evasion that allows for the application of existing model-based planning algorithms.

Nonlocal flocking dynamics: Learning the fractional order of PDEs from particle simulations

no code implementations27 Oct 2018 Zhiping Mao, Zhen Li, George Em. Karniadakis

Instead of specifying the fPDEs with an ad hoc fractional order for nonlocal flocking dynamics, we learn the effective nonlocal influence function in fPDEs directly from particle trajectories generated by the agent-based simulations.

Multivariate Density Estimation with Missing Data

1 code implementation14 Aug 2018 Zhen Li, Lili Wu, Weilian Zhou, Sujit Ghosh

Multivariate density estimation is a popular technique in statistics with wide applications including regression models allowing for heteroskedasticity in conditional variances.


SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities

4 code implementations18 Jul 2018 Zhen Li, Deqing Zou, Shouhuai Xu, Hai Jin, Yawei Zhu, Zhaoxuan Chen

Our experiments with 4 software products demonstrate the usefulness of the framework: we detect 15 vulnerabilities that are not reported in the National Vulnerability Database.

Vulnerability Detection

Deep Neural Nets with Interpolating Function as Output Activation

1 code implementation NeurIPS 2018 Bao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley J. Osher

We replace the output layer of deep neural nets, typically the softmax function, by a novel interpolating function.

VulDeePecker: A Deep Learning-Based System for Vulnerability Detection

3 code implementations5 Jan 2018 Zhen Li, Deqing Zou, Shouhuai Xu, Xinyu Ou, Hai Jin, Sujuan Wang, Zhijun Deng, Yuyi Zhong

Since deep learning is motivated to deal with problems that are very different from the problem of vulnerability detection, we need some guiding principles for applying deep learning to vulnerability detection.

Vulnerability Detection

Knowledge Concentration: Learning 100K Object Classifiers in a Single CNN

no code implementations21 Nov 2017 Jiyang Gao, Zijian, Guo, Zhen Li, Ram Nevatia

To address these challenges, we propose a Knowledge Concentration method, which effectively transfers the knowledge from dozens of specialists (multiple teacher networks) into one single model (one student network) to classify 100K object categories.

General Classification Knowledge Distillation

Understanding Hidden Memories of Recurrent Neural Networks

1 code implementation30 Oct 2017 Yao Ming, Shaozu Cao, Ruixiang Zhang, Zhen Li, Yuanzhe Chen, Yangqiu Song, Huamin Qu

We propose a technique to explain the function of individual hidden state units based on their expected response to input texts.

High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference

no code implementations ICCV 2017 Xiaoguang Han, Zhen Li, Haibin Huang, Evangelos Kalogerakis, Yizhou Yu

Our method is based on a new deep learning architecture consisting of two sub-networks: a global structure inference network and a local geometry refinement network.

Folding membrane proteins by deep transfer learning

no code implementations28 Aug 2017 Sheng Wang, Zhen Li, Yizhou Yu, Jinbo Xu

Computational elucidation of membrane protein (MP) structures is challenging partially due to lack of sufficient solved structures for homology modeling.

Transfer Learning

A Flow Model of Neural Networks

no code implementations21 Aug 2017 Zhen Li, Zuoqiang Shi

Based on a natural connection between ResNet and transport equation or its characteristic equation, we propose a continuous flow model for both ResNet and plain net.

Learning Gaussian Graphical Models Using Discriminated Hub Graphical Lasso

no code implementations17 May 2017 Zhen Li, Jingtian Bai, Weilian Zhou

When no hubs are known, we use Graphical Lasso (GL) to provide information of hubs and find that the performance of DHGL will always be better than HGL if correct prior information is given and will seldom degenerate when the prior information is wrong.

Predicting membrane protein contacts from non-membrane proteins by deep transfer learning

no code implementations24 Apr 2017 Zhen Li, Sheng Wang, Yizhou Yu, Jinbo Xu

Tested on 510 non-redundant MPs, our deep model (learned from only non-MPs) has top L/10 long-range contact prediction accuracy 0. 69, better than our deep model trained by only MPs (0. 63) and much better than a representative DCA method CCMpred (0. 47) and the CASP11 winner MetaPSICOV (0. 55).

Transfer Learning

GPU-accelerated Red Blood Cells Simulations with Transport Dissipative Particle Dynamics

2 code implementations18 Nov 2016 Ansel L. Blumers, Yu-Hang Tang, Zhen Li, Xuejin Li, George E. Karniadakis

We observe a speedup of 10. 1 on one GPU over all 16 cores within a single node, and a weak scaling efficiency of 91% across 256 nodes.

Computational Physics Biological Physics

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

1 code implementation2 Sep 2016 Sheng Wang, Siqi Sun, Zhen Li, Renyu Zhang, Jinbo Xu

Using our predicted contacts as restraints, we can (ab initio) fold 208 of the 398 membrane proteins with TMscore>0. 5.

Protein Folding

Protein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks

1 code implementation25 Apr 2016 Zhen Li, Yizhou Yu

Inspired by the recent successes of deep neural networks, in this paper, we propose an end-to-end deep network that predicts protein secondary structures from integrated local and global contextual features.

Multi-Task Learning Protein Secondary Structure Prediction

Towards Better Analysis of Deep Convolutional Neural Networks

no code implementations24 Apr 2016 Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu

Deep convolutional neural networks (CNNs) have achieved breakthrough performance in many pattern recognition tasks such as image classification.

Image Classification

LSTM-CF: Unifying Context Modeling and Fusion with LSTMs for RGB-D Scene Labeling

1 code implementation18 Apr 2016 Zhen Li, Yukang Gan, Xiaodan Liang, Yizhou Yu, Hui Cheng, Liang Lin

Another long short-term memorized fusion layer is set up to integrate the contexts along the vertical direction from different channels, and perform bi-directional propagation of the fused vertical contexts along the horizontal direction to obtain true 2D global contexts.

Scene Labeling

Blockout: Dynamic Model Selection for Hierarchical Deep Networks

no code implementations CVPR 2016 Calvin Murdock, Zhen Li, Howard Zhou, Tom Duerig

Most deep architectures for image classification--even those that are trained to classify a large number of diverse categories--learn shared image representations with a single model.

General Classification Image Classification +1

Learning Locally-Adaptive Decision Functions for Person Verification

no code implementations CVPR 2013 Zhen Li, Shiyu Chang, Feng Liang, Thomas S. Huang, Liangliang Cao, John R. Smith

This paper proposes to learn a decision function for verification that can be viewed as a joint model of a distance metric and a locally adaptive thresholding rule.

Face Verification Metric Learning +1

Learning to Search Efficiently in High Dimensions

no code implementations NeurIPS 2011 Zhen Li, Huazhong Ning, Liangliang Cao, Tong Zhang, Yihong Gong, Thomas S. Huang

Traditional approaches relied on algorithmic constructions that are often data independent (such as Locality Sensitive Hashing) or weakly dependent (such as kd-trees, k-means trees).

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