Xiaofei He

article

Physical exercise‐induced circAnks1b upregulation promotes protective endoplasmic reticulum stress and suppresses apoptosis via miR‐130b‐5p/Pak2 signaling in an ischemic stroke model

Xiaofeng Yang, Yating Mu, Yifeng Feng, Mingyue Li, more

CNS Neuroscience & Therapeutics > 30 > 9 > n/a - n/a

Aims Physical exercise (PE) can accelerate post‐stroke recovery. This study investigated contributions of circRNAs to PE‐induced improvements in post‐stroke neurological function. Methods Rats subjected to transient middle cerebral artery occlusion were left sedentary or provided running‐wheel access for 4 weeks during recovery. CircRNAs from peri‐infarct cortex were identified by high‐throughput...

article

The role of bile acid receptor TGR5 in regulating inflammatory signalling

Daijiao Ye, Jiayao He, Xiaofei He

Scandinavian Journal of Immunology > 99 > 4 > n/a - n/a

Takeda G protein‐coupled receptor 5 (TGR5) is a bile acid receptor, and its role in regulating metabolism after binding with bile acids has been established. Since the immune response depends on metabolism to provide biomolecules and energy to cope with challenging conditions, emerging evidence reveals the regulatory effects of TGR5 on the immune response. An in‐depth understanding of the effect of...

article

Co‐Ni‐P‐B catalyzed hydroformylation of long linear α olefins

Jing Guo, Xiaofei He, Subing Fan, Xinhua Gao, more

Journal of Chemical Technology & Biotechnology > 96 > 7 > 1974 - 1980

BACKGROUND As indirect liquefaction of coal has been carried out in megaton scale, extension of the Fischer‐Tropsch synthesis products has received renewed interest. Hydroformylation provides a way for the transformation of alkenes to aldehydes. Homogeneous rhodium complex catalysts are efficacious but expensive and not easy to recover and reuse. Heterogeneous catalysts are desired to enable their...

article

Multi-label active learning based on submodular functions

Kuoliang Wu, Deng Cai, Xiaofei He

Neurocomputing > 2018 > 313 > C > 436-442

In the data collection task, it is more expensive to annotate the instance in multi-label learning problem, since each instance is associated with multiple labels. Therefore it is more important to adopt active learning method in multi-label learning to reduce the labeling cost. Recent researches indicate submodular function optimization works well on subset selection problem and provides theoretical...

article

How Do Women View Risk-Based Mammography Screening? A Qualitative Study

Xiaofei He, Karen E. Schifferdecker, Elissa M. Ozanne, Anna N. A. Tosteson, more

Journal of General Internal Medicine > 2018 > 33 > 11 > 1905-1912

Background Decades of persuasive messages have reinforced the importance of traditional screening mammography at regular intervals. A potential new paradigm, risk-based screening, adjusts mammography frequency based on a woman’s estimated breast cancer risk in order to maximize mortality reduction while minimizing false positives and overdiagnosis. Women’s views of risk-based screening are unknown...

article

Real-Time Object Tracking on a Drone With Multi-Inertial Sensing Data

Peng Chen, Yuanjie Dang, Ronghua Liang, Wei Zhu, more

IEEE Transactions on Intelligent Transportation Systems > 2018 > 19 > 1 > 131 - 139

Real-time object tracking on a drone under a dynamic environment has been a challenging issue for many years, with existing approaches using off-line calculation or powerful computation units on board. This paper presents a new lightweight real-time onboard object tracking approach with multi-inertial sensing data, wherein a highly energy-efficient drone is built based on the Snapdragon flight board...

article

Weakly-Supervised Deep Embedding for Product Review Sentiment Analysis

Wei Zhao, Ziyu Guan, Long Chen, Xiaofei He, more

IEEE Transactions on Knowledge and Data Engineering > 2018 > 30 > 1 > 185 - 197

Product reviews are valuable for upcoming buyers in helping them make decisions. To this end, different opinion mining techniques have been proposed, where judging a review sentence's orientation (e.g., positive or negative) is one of their key challenges. Recently, deep learning has emerged as an effective means for solving sentiment classification problems. A neural network intrinsically learns...

article

Sparse Learning with Stochastic Composite Optimization

Weizhong Zhang, Lijun Zhang, Zhongming Jin, Rong Jin, more

IEEE Transactions on Pattern Analysis and Machine Intelligence > 2017 > 39 > 6 > 1223 - 1236

In this paper, we study Stochastic Composite Optimization (SCO) for sparse learning that aims to learn a sparse solution from a composite function. Most of the recent SCO algorithms have already reached the optimal expected convergence rate $\mathcal {O}(1/\lambda T)$<alternatives> <inline-graphic xlink:href="zhang-ieq1-2578323.gif"/></alternatives>, but they often fail...

chapter

A real-time 17-scale object detection accelerator with adaptive 2000-stage classification in 65nm CMOS

Minkyu Kim, Abinash Mohanty, Deepak Kadetotad, Naveen Suda, more

2017 IEEE International Symposium on Circuits and Systems (ISCAS) > 1 - 4

2017 IEEE International Symposium on Circuits and Systems (ISCAS)

This paper presents an object detection accelerator that features many-scale (17), many-object (up to 50), multi-class (e.g., face, traffic sign), and high accuracy (average precision of 0.79/0.65 for AFW/BTSD datasets). Employing 10 gradient/color channels, integral features are extracted, and the results of 2,000 simple classifiers for rigid boosted templates are adaptively combined to make a strong...

chapter

A real-time 17-scale object detection accelerator with adaptive 2000-stage classification in 65nm CMOS

Minkyu Kim, Abinash Mohanty, Deepak Kadetotad, Naveen Suda, more

2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC) > 21 - 22

2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC)

This paper presents an object detection accelerator that features many-scale (17), many-object (up to 50), multi-class (e.g., face, traffic sign), and high accuracy (average precision (AP) of 0.81/0.72 for AFW/BTSD datasets) detection. Employing 10 gradient/color channels, integral features are extracted and 2,000 simple classifiers for rigid boosted templates are adaptively combined to make a strong...

article

Heterogeneous hypergraph embedding for document recommendation

Yu Zhu, Ziyu Guan, Shulong Tan, Haifeng Liu, more

Neurocomputing > 2016 > 216 > 150-162

Nowadays, more and more users are using online tagging services to organize their resources, e.g. Web bookmarks and bibliographies. Tags not only facilitate organization and retrieval of resources, but also provide valuable semantic descriptions for both resources and users’ interests. This work is focused on document recommendation using tagging data. Previous works either model the 3-order relation...

article

Heterogeneous hypergraph embedding for document recommendation

Yu Zhu, Ziyu Guan, Shulong Tan, Haifeng Liu, more

Neurocomputing > 2016 > 216 > C > 150-162

Nowadays, more and more users are using online tagging services to organize their resources, e.g. Web bookmarks and bibliographies. Tags not only facilitate organization and retrieval of resources, but also provide valuable semantic descriptions for both resources and users’ interests. This work is focused on document recommendation using tagging data. Previous works either model the 3-order relation...

article

Parallel implementation and optimization of high definition video real-time dehazing

Huailiang Tan, Xiaofei He, Zijian Wang, Gaoming Liu

Multimedia Tools and Applications > 2017 > 76 > 22 > 23413- 23434

In some warning applications, such as aircraft taking-off and landing, ship sailing, and traffic guidance in foggy weather, the high definition (HD) and rapid dehazing of images and videos is increasingly necessary. Existing technologies for the dehazing of videos or images have not completely exploited the parallel computing capacity of modern multi-core CPU and GPU, and leads to the long dehazing...

article

Existence and multiplicity of homoclinic solutions for second‐order nonlinear difference equations with Jacobi operators

Peng Chen, Xiaofei He

Mathematical Methods in the Applied Sciences > 39 > 18 > 5705 - 5719

In this paper, a nonperiodic discrete nonlinear equation with Jacobi operators is considered. By using the critical point theory, we establish some new sufficient conditions on the existence and multiplicity of homoclinic solutions. Recent results are generalized and significantly improved. Furthermore, our results greatly improve some existing ones even for some special cases. Copyright © 2016 John...

article

Tracking people in RGBD videos using deep learning and motion clues

Hongyang Xue, Yao Liu, Deng Cai, Xiaofei He

Neurocomputing > 2016 > 204 > C > 70-76

Tracking people in videos is an important topic in surveillance. We consider the problem of human tracking in RGBD videos filmed by sensors such as MS Kinect and Primesense. Our goal is to track persons where the crowd of people is known in advance or all persons in the video have appeared in the very beginning. Thus we can train a classifier to help classify and track persons across the video. A...

article

Local Feature Discriminant Projection

Mengyang Yu, Ling Shao, Xiantong Zhen, Xiaofei He

IEEE Transactions on Pattern Analysis and Machine Intelligence > 2016 > 38 > 9 > 1908 - 1914

In this paper, we propose a novel subspace learning algorithm called Local Feature Discriminant Projection (LFDP) for supervised dimensionality reduction of local features. LFDP is able to efficiently seek a subspace to improve the discriminability of local features for classification. We make three novel contributions. First, the proposed LFDP is a general supervised subspace learning algorithm which...

article

User Preference Learning for Online Social Recommendation

Zhou Zhao, Hanqing Lu, Deng Cai, Xiaofei He, more

IEEE Transactions on Knowledge and Data Engineering > 2016 > 28 > 9 > 2522 - 2534

A social recommendation system has attracted a lot of attention recently in the research communities of information retrieval, machine learning, and data mining. Traditional social recommendation algorithms are often based on batch machine learning methods which suffer from several critical limitations, e.g., extremely expensive model retraining cost whenever new user ratings arrive, unable to capture...

article

Improving Collaborative Recommendation via User-Item Subgroups

Jiajun Bu, Xin Shen, Bin Xu, Chun Chen, more

IEEE Transactions on Knowledge and Data Engineering > 2016 > 28 > 9 > 2363 - 2375

Collaborative filtering (CF) is out of question the most widely adopted and successful recommendation approach. A typical CF-based recommender system associates a user with a group of like-minded users based on their individual preferences over all the items, either explicit or implicit, and then recommends to the user some unobserved items enjoyed by the group. However, we find that two users with...

chapter

A Game-Theoretic Model on Coalitional Attacks in Smart Grid

Xinyu Yang, Xiaofei He, Jie Lin, Wei Yu, more

2016 IEEE Trustcom/BigDataSE/ISPA > 435 - 442

2016 IEEE Trustcom/BigDataSE/ISPA

The diverse cyber attacks, that make operation of the smart grid challenging, must be addressed before wide adoption of smart grids can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the design of a specific defensive strategy to deal with a specific threat. In this paper we address the issue of...

article

A-Optimal Projection for Image Representation

Xiaofei He, Chiyuan Zhang, Lijun Zhang, Xuelong Li

IEEE Transactions on Pattern Analysis and Machine Intelligence > 2016 > 38 > 5 > 1009 - 1015

We consider the problem of image representation from the perspective of statistical design. Recent studies have shown that images are possibly sampled from a low dimensional manifold despite of the fact that the ambient space is usually very high dimensional. Learning low dimensional image representations is crucial for many image processing tasks such as recognition and retrieval. Most of the existing...

INFONA - science communication portal

Search results for: Xiaofei He

Physical exercise‐induced circAnks1b upregulation promotes protective endoplasmic reticulum stress and suppresses apoptosis via miR‐130b‐5p/Pak2 signaling in an ischemic stroke model

The role of bile acid receptor TGR5 in regulating inflammatory signalling

Co‐Ni‐P‐B catalyzed hydroformylation of long linear α olefins

Multi-label active learning based on submodular functions

How Do Women View Risk-Based Mammography Screening? A Qualitative Study

Real-Time Object Tracking on a Drone With Multi-Inertial Sensing Data

Weakly-Supervised Deep Embedding for Product Review Sentiment Analysis

Sparse Learning with Stochastic Composite Optimization

A real-time 17-scale object detection accelerator with adaptive 2000-stage classification in 65nm CMOS

A real-time 17-scale object detection accelerator with adaptive 2000-stage classification in 65nm CMOS

Heterogeneous hypergraph embedding for document recommendation

Heterogeneous hypergraph embedding for document recommendation

Parallel implementation and optimization of high definition video real-time dehazing

Existence and multiplicity of homoclinic solutions for second‐order nonlinear difference equations with Jacobi operators

Tracking people in RGBD videos using deep learning and motion clues

Local Feature Discriminant Projection

User Preference Learning for Online Social Recommendation

Improving Collaborative Recommendation via User-Item Subgroups

A Game-Theoretic Model on Coalitional Attacks in Smart Grid

A-Optimal Projection for Image Representation

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