Search Results for author: Lei Shi

Found 71 papers, 16 papers with code

Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition

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.

Action Recognition Skeleton Based Action Recognition

Improving Self-supervised Molecular Representation Learning using Persistent Homology

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.

A Comparative Analysis of the COVID-19 Infodemic in English and Chinese: Insights from Social Media Textual Data

no code implementations14 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.

Misinformation Sentiment Analysis

$\mathbb{VD}$-$\mathbb{GR}$: Boosting $\mathbb{V}$isual $\mathbb{D}$ialog with Cascaded Spatial-Temporal Multi-Modal $\mathbb{GR}$aphs

no code implementations25 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).

Visual Dialog

GraphGPT: Graph Instruction Tuning for Large Language Models

1 code implementation19 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.

Data Augmentation Graph Learning +2

Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels

1 code implementation8 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.


Solving PDEs on Spheres with Physics-Informed Convolutional Neural Networks

no code implementations18 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.

Classification with Deep Neural Networks and Logistic Loss

no code implementations31 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.

Binary Classification Classification +1

OSP: Boosting Distributed Model Training with 2-stage Synchronization

no code implementations29 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.

Encoding Enhanced Complex CNN for Accurate and Highly Accelerated MRI

no code implementations21 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.

MRI Reconstruction

Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs

1 code implementation24 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.

Optimality of Robust Online Learning

no code implementations20 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).


Pairwise Ranking with Gaussian Kernels

no code implementations6 Apr 2023 Guanhang Lei, Lei Shi

Regularized pairwise ranking with Gaussian kernels is one of the cutting-edge learning algorithms.

Cross-modal information fusion for voice spoofing detection

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.

Automatic Speech Recognition fake voice detection +3

Exit options sustain altruistic punishment and decrease the second-order free-riders, but it is not a panacea

no code implementations12 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.

Open-Ended Question Answering

Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generation

1 code implementation5 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.

Paraphrase Generation

Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression

no code implementations20 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.


Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate

1 code implementation14 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.

Capacity dependent analysis for functional online learning algorithms

no code implementations25 Sep 2022 Xin Guo, Zheng-Chu Guo, Lei Shi

This article provides convergence analysis of online stochastic gradient descent algorithms for functional linear models.

INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations

no code implementations2 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

Coefficient-based Regularized Distribution Regression

no code implementations26 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.


Solving parametric partial differential equations with deep rectified quadratic unit neural networks

no code implementations14 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.

Learning with Asymmetric Kernels: Least Squares and Feature Interpretation

no code implementations3 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.

Dense Contrastive Visual-Linguistic Pretraining

no code implementations24 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.

Contrastive Learning Data Augmentation +2

Provably Accelerated Decentralized Gradient Method Over Unbalanced Directed Graphs

no code implementations26 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.

Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks

no code implementations14 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.

Multi-modal Scene-compliant User Intention Estimation in Navigation

no code implementations13 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.

Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums

no code implementations26 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.

Variational Inference

AdaSGN: Adapting Joint Number and Model Size for Efficient Skeleton-Based Action Recognition

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.

Action Recognition Skeleton Based Action Recognition

Topological charge engineering in lasing bound states in continuum

no code implementations31 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.


Fast algorithms for robust principal component analysis with an upper bound on the rank

1 code implementation18 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.

Vocal Bursts Type Prediction

Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week's Activities

no code implementations12 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.

Social Interactions Clustering MOOC Students: An Exploratory Study

no code implementations10 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?"

BIG-bench Machine Learning Clustering

Contrastive Visual-Linguistic Pretraining

no code implementations26 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.

Contrastive Learning regression +2

Leader-Driven Opinion Dynamics in Signed Social Networks With Asynchronous Trust/Distrust Level Evolution

no code implementations19 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.

Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action Recognition

1 code implementation7 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.

Action Recognition Skeleton Based Action Recognition +1

Analysis of Regularized Least Squares in Reproducing Kernel Krein Spaces

no code implementations1 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).

What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition

no code implementations7 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.

Action Recognition Gesture Recognition +2

Sub/super-stochastic matrix with applications to bipartite tracking control over signed networks

no code implementations4 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.

Mobility Inference on Long-Tailed Sparse Trajectory

no code implementations21 Jan 2020 Lei Shi

How can we infer such a mobility model from the single trajectory information?

Multi-Layer Content Interaction Through Quaternion Product For Visual Question Answering

no code implementations3 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.

Question Answering Video Description +1

Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks

3 code implementations15 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.

Action Recognition graph construction +2

Action Recognition via Pose-Based Graph Convolutional Networks with Intermediate Dense Supervision

no code implementations28 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.

Action Recognition Skeleton Based Action Recognition +1

Non-Local Graph Convolutional Networks for Skeleton-Based 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.

Action Recognition Skeleton Based Action Recognition

Gaussian Mixture Marginal Distributions for Modelling Remaining Pipe Wall Thickness of Critical Water Mains in Non-Destructive Evaluation

no code implementations2 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.

Gaussian Processes

Skeleton-Based Action Recognition With Directed Graph Neural Networks

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.

Action Recognition Skeleton Based Action Recognition +1

MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks

1 code implementation15 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.

Anomaly Detection BIG-bench Machine Learning +2

Realizing data features by deep nets

no code implementations1 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.

Generalization Properties of hyper-RKHS and its Applications

no code implementations26 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.

Learning Theory regression

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

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.

graph construction Skeleton Based Action Recognition +1

Fast and Strong Convergence of Online Learning Algorithms

no code implementations10 Oct 2017 Zheng-Chu Guo, Lei Shi

In this paper, we study the online learning algorithm without explicit regularization terms.

Convergence of Unregularized Online Learning Algorithms

no code implementations9 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.

Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network

no code implementations7 Aug 2017 Zheng-Chu Guo, Lei Shi, Qiang Wu

Regularization kernel network is an effective and widely used method for nonlinear regression analysis.

Learning Theory regression

Real-time 3D Human Tracking for Mobile Robots with Multisensors

no code implementations15 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).

Sensor Fusion Visual Tracking

Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction

no code implementations3 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.

Compressive Sensing Computed Tomography (CT) +1

Latent Topic Embedding

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.

Topic Models Word Embeddings

A Novel Artificial Fish Swarm Algorithm for Pattern Recognition with Convex Optimization

no code implementations1 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.

Functional Hashing for Compressing Neural Networks

no code implementations20 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.

Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks

no code implementations22 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.

Classification General Classification +3

Place classification with a graph regularized deep neural network model

no code implementations12 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.

Classification General Classification

Sparse Additive Text Models with Low Rank Background

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.

Bayesian Probabilistic Co-Subspace Addition

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.

Variational Inference

Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling

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.

Bayesian Inference

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