1 code implementation • ECCV 2020 • Ke Cheng, Yifan Zhang, Congqi Cao, Lei Shi, Jian Cheng, Hanqing Lu
Nevertheless, how to efficiently model the spatial-temporal skeleton graph without introducing extra computation burden is a challenging problem for industrial deployment.
1 code implementation • NeurIPS 2023 • Yuankai Luo, Lei Shi, Veronika Thost
Self-supervised learning (SSL) has great potential for molecular representation learning given the complexity of molecular graphs, the large amounts of unlabelled data available, the considerable cost of obtaining labels experimentally, and the hence often only small training datasets.
no code implementations • 14 Nov 2023 • Jia Luo, Daiyun Peng, Lei Shi, Didier El Baz, Xinran Liu
This paper presents a comparative analysis of the COVID-19 infodemic in the English and Chinese languages, utilizing textual data extracted from social media platforms.
no code implementations • 25 Oct 2023 • Adnen Abdessaied, Lei Shi, Andreas Bulling
We propose $\mathbb{VD}$-$\mathbb{GR}$ - a novel visual dialog model that combines pre-trained language models (LMs) with graph neural networks (GNNs).
1 code implementation • 19 Oct 2023 • Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Lixin Su, Suqi Cheng, Dawei Yin, Chao Huang
In this work, we present the GraphGPT framework that aligns LLMs with graph structural knowledge with a graph instruction tuning paradigm.
1 code implementation • 8 Oct 2023 • Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens
To enhance kernel flexibility, this paper introduces the concept of Locally-Adaptive-Bandwidths (LAB) as trainable parameters to enhance the Radial Basis Function (RBF) kernel, giving rise to the LAB RBF kernel.
no code implementations • 18 Aug 2023 • Guanhang Lei, Zhen Lei, Lei Shi, Chenyu Zeng, Ding-Xuan Zhou
In this paper, we establish rigorous analysis of the physics-informed convolutional neural network (PICNN) for solving PDEs on the sphere.
no code implementations • 31 Jul 2023 • Zihan Zhang, Lei Shi, Ding-Xuan Zhou
In this paper, we aim to fill this gap by establishing a novel and elegant oracle-type inequality, which enables us to deal with the boundedness restriction of the target function, and using it to derive sharp convergence rates for fully connected ReLU DNN classifiers trained with logistic loss.
no code implementations • 29 Jun 2023 • Zixuan Chen, Lei Shi, Xuandong Liu, Jiahui Li, Sen Liu, Yang Xu
However, these two types of methods can result in accuracy loss due to discarded gradients and have limited enhancement on the throughput of model synchronization, respectively.
no code implementations • 21 Jun 2023 • Zimeng Li, Sa Xiao, Cheng Wang, Haidong Li, Xiuchao Zhao, Caohui Duan, Qian Zhou, Qiuchen Rao, Yuan Fang, Junshuai Xie, Lei Shi, Fumin Guo, Chaohui Ye, Xin Zhou
Magnetic resonance imaging (MRI) using hyperpolarized noble gases provides a way to visualize the structure and function of human lung, but the long imaging time limits its broad research and clinical applications.
no code implementations • 25 Apr 2023 • Lei Shi, Tianyu Gao, Zheng Zhang, Junxing Zhang
Deep learning based models for medical image segmentation have made great progress in recent years.
1 code implementation • 24 Apr 2023 • Yuankai Luo, Lei Shi, Mufan Xu, Yuwen Ji, Fengli Xiao, Chunming Hu, Zhiguang Shan
Experiment outcomes show that the F1 score of best GF profile significantly outperforms alternative methods of impact indicators and bibliometric networks in all the 6 computer science fields considered.
no code implementations • 20 Apr 2023 • Zheng-Chu Guo, Andreas Christmann, Lei Shi
In this paper, we study an online learning algorithm with a robust loss function $\mathcal{L}_{\sigma}$ for regression over a reproducing kernel Hilbert space (RKHS).
no code implementations • 6 Apr 2023 • Guanhang Lei, Lei Shi
Regularized pairwise ranking with Gaussian kernels is one of the cutting-edge learning algorithms.
1 code implementation • journal 2023 • Junxiao Xue, Hao Zhou, Huawei Song, Bin Wu, Lei Shi
Researchers have proposed many methods to defend against these attacks, but in the existing methods, researchers just focus on speech features.
Ranked #1 on
Voice Anti-spoofing
on ASVspoof 2019 - PA
no code implementations • 12 Jan 2023 • Chen Shen, Zhao Song, Lei Shi, Jun Tanimoto, Zhen Wang
Altruistic punishment, where individuals incur personal costs to punish others who have harmed third parties, presents an evolutionary conundrum as it undermines individual fitness.
1 code implementation • 5 Jan 2023 • Jialin Yu, Alexandra I. Cristea, Anoushka Harit, Zhongtian Sun, Olanrewaju Tahir Aduragba, Lei Shi, Noura Al Moubayed
To leverage information from text pairs, we additionally introduce a novel supervised model we call dual directional learning (DDL), which is designed to integrate with our proposed VSAR model.
no code implementations • 20 Nov 2022 • Jiading Liu, Lei Shi
Previous analysis of regularized functional linear regression in a reproducing kernel Hilbert space (RKHS) typically requires the target function to be contained in this kernel space.
1 code implementation • 14 Oct 2022 • Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
In the proposed family, EquiStatic has a degree of $\Theta(\ln(n))$, where $n$ is the network size, and a series of time-dependent one-peer topologies, EquiDyn, has a constant degree of 1.
no code implementations • 25 Sep 2022 • Xin Guo, Zheng-Chu Guo, Lei Shi
This article provides convergence analysis of online stochastic gradient descent algorithms for functional linear models.
no code implementations • 2 Sep 2022 • Jialin Yu, Alexandra I. Cristea, Anoushka Harit, Zhongtian Sun, Olanrewaju Tahir Aduragba, Lei Shi, Noura Al Moubayed
XAI with natural language processing aims to produce human-readable explanations as evidence for AI decision-making, which addresses explainability and transparency.
Decision Making
Explainable Artificial Intelligence (XAI)
+2
no code implementations • 26 Aug 2022 • Yuan Mao, Lei Shi, Zheng-Chu Guo
Compared with the kernel methods for distribution regression in the literature, the algorithm under consideration does not require the kernel to be symmetric and positive semi-definite and hence provides a simple paradigm for designing indefinite kernel methods, which enriches the theme of the distribution regression.
no code implementations • 19 Apr 2022 • Zaiyun Lin, Shiqiu Yin, Lei Shi, Wenbiao Zhou, YingSheng Zhang
Retrosynthesis prediction is one of the fundamental challenges in organic chemistry and related fields.
no code implementations • 14 Mar 2022 • Zhen Lei, Lei Shi, Chenyu Zeng
In this study, we investigate the expressive power of deep rectified quadratic unit (ReQU) neural networks for approximating the solution maps of parametric PDEs.
no code implementations • 3 Feb 2022 • Mingzhen He, Fan He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens
Asymmetric kernels naturally exist in real life, e. g., for conditional probability and directed graphs.
no code implementations • 24 Sep 2021 • Lei Shi, Bin Wang, Junxing Zhang
Diabetic retinopathy (DR) is one of the major blindness-causing diseases currently known.
no code implementations • 24 Sep 2021 • Lei Shi, Kai Shuang, Shijie Geng, Peng Gao, Zuohui Fu, Gerard de Melo, Yunpeng Chen, Sen Su
To overcome these issues, we propose unbiased Dense Contrastive Visual-Linguistic Pretraining (DCVLP), which replaces the region regression and classification with cross-modality region contrastive learning that requires no annotations.
no code implementations • 26 Jul 2021 • Zhuoqing Song, Lei Shi, Shi Pu, Ming Yan
In this work, we consider the decentralized optimization problem in which a network of $n$ agents, each possessing a smooth and convex objective function, wish to collaboratively minimize the average of all the objective functions through peer-to-peer communication in a directed graph.
no code implementations • 14 Jun 2021 • Zhuoqing Song, Lei Shi, Shi Pu, Ming Yan
The second algorithm is a broadcast-like version of CPP (B-CPP), and it also achieves linear convergence rate under the same conditions on the objective functions.
no code implementations • 13 Jun 2021 • Kavindie Katuwandeniya, Stefan H. Kiss, Lei Shi, Jaime Valls Miro
A multi-modal framework to generate user intention distributions when operating a mobile vehicle is proposed in this work.
no code implementations • 26 Apr 2021 • Jialin Yu, Laila Alrajhi, Anoushka Harit, Zhongtian Sun, Alexandra I. Cristea, Lei Shi
Learners may post their feelings of confusion and struggle in the respective MOOC forums, but with the large volume of posts and high workloads for MOOC instructors, it is unlikely that the instructors can identify all learners requiring intervention.
no code implementations • ICCV 2021 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
Existing methods for skeleton-based action recognition mainly focus on improving the recognition accuracy, whereas the efficiency of the model is rarely considered.
no code implementations • 31 Dec 2020 • Sughra Mohamed, Jie Wang, Heikki Rekola, Janne Heikkinen, Benjamin Asamoah, Lei Shi, Tommi K. Hakala
We experimentally analyze all four observed lasing BICs by imaging their far-field polarization vortices and their associated topological charges.
Optics
1 code implementation • 18 Aug 2020 • Ningyu Sha, Lei Shi, Ming Yan
The first type of algorithm applies regularization terms on the singular values of a matrix to obtain a low-rank matrix.
no code implementations • 12 Aug 2020 • Ahmed Alamri, Mohammad Alshehri, Alexandra I. Cristea, Filipe D. Pereira, Elaine Oliveira, Lei Shi, Craig Stewart
While Massive Open Online Course (MOOCs) platforms provide knowledge in a new and unique way, the very high number of dropouts is a significant drawback.
no code implementations • 12 Aug 2020 • Lei Shi, Alexandra I. Cristea, Armando M. Toda, Wilk Oliveira
Massive Open Online Courses (MOOCs) exhibit a remarkable heterogeneity of students.
no code implementations • 10 Aug 2020 • Lei Shi, Alexandra Cristea, Ahmad Alamri, Armando M. Toda, Wilk Oliveira
An exploratory study on social interactions of MOOC students in FutureLearn was conducted, to answer "how can we cluster students based on their social interactions?"
no code implementations • 26 Jul 2020 • Lei Shi, Kai Shuang, Shijie Geng, Peng Su, Zhengkai Jiang, Peng Gao, Zuohui Fu, Gerard de Melo, Sen Su
We evaluate CVLP on several down-stream tasks, including VQA, GQA and NLVR2 to validate the superiority of contrastive learning on multi-modality representation learning.
no code implementations • 19 Jul 2020 • Lei Shi, Yuhua Cheng, Jinliang Shao, Xiaofan Wang, Hanmin Sheng
Trust and distrust are common in the opinion interactions among agents in social networks, and they are described by the edges with positive and negative weights in the signed digraph, respectively.
1 code implementation • 7 Jul 2020 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
Besides, from the data aspect, we introduce a skeletal data decoupling technique to emphasize the specific characteristics of space/time and different motion scales, resulting in a more comprehensive understanding of the human actions. To test the effectiveness of the proposed method, extensive experiments are conducted on four challenging datasets for skeleton-based gesture and action recognition, namely, SHREC, DHG, NTU-60 and NTU-120, where DSTA-Net achieves state-of-the-art performance on all of them.
Ranked #22 on
Skeleton Based Action Recognition
on NTU RGB+D
no code implementations • 1 Jun 2020 • Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
In this paper, we study the asymptotic properties of regularized least squares with indefinite kernels in reproducing kernel Krein spaces (RKKS).
no code implementations • 7 Apr 2020 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
The two perspectives are orthogonal and complementary to each other; and by fusing them in a unified framework, our method achieves a more comprehensive understanding of the skeleton data.
no code implementations • 4 Apr 2020 • Lei Shi, Wei Xing Zheng, Jinliang Shao, Yuhua Cheng
In the first part, we examine the dynamics of bipartite tracking for first-order MASs, second-order MASs and general linear MASs in the presence of asynchronous interactions, respectively.
no code implementations • 21 Jan 2020 • Lei Shi
How can we infer such a mobility model from the single trajectory information?
no code implementations • 3 Jan 2020 • Lei Shi, Shijie Geng, Kai Shuang, Chiori Hori, Songxiang Liu, Peng Gao, Sen Su
To solve the issue for the intermediate layers, we propose an efficient Quaternion Block Network (QBN) to learn interaction not only for the last layer but also for all intermediate layers simultaneously.
3 code implementations • 15 Dec 2019 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
Second, the second-order information of the skeleton data, i. e., the length and orientation of the bones, is rarely investigated, which is naturally more informative and discriminative for the human action recognition.
no code implementations • 28 Nov 2019 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
Existing methods exploit the joint positions to extract the body-part features from the activation map of the convolutional networks to assist human action recognition.
1 code implementation • arXiv 2019 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
However, the topology of the graph is set by hand and fixed over all layers, which may be not optimal for the action recognition task and the hierarchical CNN structures.
Ranked #50 on
Skeleton Based Action Recognition
on NTU RGB+D
no code implementations • 2 Jul 2019 • Linh Nguyen, Jaime Valls Miro, Lei Shi, Teresa Vidal-Calleja
Rapidly estimating the remaining wall thickness (RWT) is paramount for the non-destructive condition assessment evaluation of large critical metallic pipelines.
1 code implementation • CVPR 2019 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
The skeleton data have been widely used for the action recognition tasks since they can robustly accommodate dynamic circumstances and complex backgrounds.
Ranked #7 on
Skeleton Based Action Recognition
on UAV-Human
1 code implementation • 23 Apr 2019 • Cihan Dogan, Aimore Dutra, Adam Gara, Alfredo Gemma, Lei Shi, Michael Sigamani, Ella Walters
Fine-grained Named Entity Recognition is a task whereby we detect and classify entity mentions to a large set of types.
1 code implementation • 15 Jan 2019 • Dan Li, Dacheng Chen, Lei Shi, Baihong Jin, Jonathan Goh, See-Kiong Ng
The prevalence of networked sensors and actuators in many real-world systems such as smart buildings, factories, power plants, and data centers generate substantial amounts of multivariate time series data for these systems.
no code implementations • 1 Jan 2019 • Zheng-Chu Guo, Lei Shi, Shao-Bo Lin
Based on refined covering number estimates, we find that, to realize some complex data features, deep nets can improve the performances of shallow neural networks (shallow nets for short) without requiring additional capacity costs.
no code implementations • 26 Sep 2018 • Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
This paper generalizes regularized regression problems in a hyper-reproducing kernel Hilbert space (hyper-RKHS), illustrates its utility for kernel learning and out-of-sample extensions, and proves asymptotic convergence results for the introduced regression models in an approximation theory view.
4 code implementations • CVPR 2019 • Lei Shi, Yifan Zhang, Jian Cheng, Hanqing Lu
In addition, the second-order information (the lengths and directions of bones) of the skeleton data, which is naturally more informative and discriminative for action recognition, is rarely investigated in existing methods.
Ranked #3 on
3D Action Recognition
on Assembly101
no code implementations • 10 Oct 2017 • Zheng-Chu Guo, Lei Shi
In this paper, we study the online learning algorithm without explicit regularization terms.
no code implementations • 9 Aug 2017 • Yunwen Lei, Lei Shi, Zheng-Chu Guo
In this paper we study the convergence of online gradient descent algorithms in reproducing kernel Hilbert spaces (RKHSs) without regularization.
no code implementations • 7 Aug 2017 • Zheng-Chu Guo, Lei Shi, Qiang Wu
Regularization kernel network is an effective and widely used method for nonlinear regression analysis.
no code implementations • 15 Mar 2017 • Mengmeng Wang, Daobilige Su, Lei Shi, Yong liu, Jaime Valls Miro
An ultrasonic sensor array is employed to provide the range information from the target person to the robot and Gaussian Process Regression is used for partial location estimation (2-D).
no code implementations • 3 Jan 2017 • Xiaolin Huang, Yan Xia, Lei Shi, Yixing Huang, Ming Yan, Joachim Hornegger, Andreas Maier
Aiming at overexposure correction for computed tomography (CT) reconstruction, we in this paper propose a mixed one-bit compressive sensing (M1bit-CS) to acquire information from both regular and saturated measurements.
no code implementations • COLING 2016 • Di Jiang, Lei Shi, Rongzhong Lian, Hua Wu
Topic modeling and word embedding are two important techniques for deriving latent semantics from data.
no code implementations • 1 Dec 2016 • Lei Shi, Rui Guo, Yuchen Ma
Among these parameters, visual and step are very significant in view of the fact that artificial fish basically move based on these parameters.
no code implementations • 20 May 2016 • Lei Shi, Shikun Feng, ZhifanZhu
As the complexity of deep neural networks (DNNs) trend to grow to absorb the increasing sizes of data, memory and energy consumption has been receiving more and more attentions for industrial applications, especially on mobile devices.
no code implementations • 22 Sep 2015 • Yiyi Liao, Sarath Kodagoda, Yue Wang, Lei Shi, Yong liu
As scene images have larger diversity than the iconic object images, it is more challenging for deep learning methods to automatically learn features from scene images with less samples.
no code implementations • 12 Jun 2015 • Yiyi Liao, Sarath Kodagoda, Yue Wang, Lei Shi, Yong liu
Furthermore, results show that the features automatically learned from the raw input range data can achieve competitive results to the features constructed based on statistical and geometrical information.
no code implementations • 14 May 2015 • Xiaolin Huang, Lei Shi, Ming Yan, Johan A. K. Suykens
The one-sided $\ell_1$ loss and the linear loss are two popular loss functions for 1bit-CS.
no code implementations • 27 Aug 2014 • Yuyu Zhang, Liang Pang, Lei Shi, Bin Wang
This paper describes the solution of Bazinga Team for Tmall Recommendation Prize 2014.
no code implementations • NeurIPS 2013 • Lei Shi
This paper extends to propose sparse additive model with low rank background (SAM-LRB), and simple yet efficient estimation.
no code implementations • NeurIPS 2012 • Lei Shi
Furthermore, PCSA is extended to tackling and filling missing values, to adapting its sparseness, and to modelling tensor data.
no code implementations • NeurIPS 2009 • Lei Shi, Thomas L. Griffiths
Here we propose a simple mechanism for Bayesian inference which involves averaging over a few feature detection neurons which fire at a rate determined by their similarity to a sensory stimulus.