b'Lei Shi'

research

∙ 04/19/2022

G2GT: Retrosynthesis Prediction with Graph to Graph Attention Neural Network and Self-Training

Retrosynthesis prediction is one of the fundamental challenges in organi...

Zaiyun Lin, et al. ∙

research

∙ 03/14/2022

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

Implementing deep neural networks for learning the solution maps of para...

Zhen Lei, et al. ∙

research

∙ 02/24/2022

Tactile Materials in Practice: Understanding the Experiences of Teachers of the Visually Impaired

Teachers of the visually impaired (TVIs) regularly present tactile mater...

Mahika Phutane, et al. ∙

research

∙ 02/03/2022

Learning with Asymmetric Kernels: Least Squares and Feature Interpretation

Asymmetric kernels naturally exist in real life, e.g., for conditional p...

Mingzhen He, et al. ∙

research

∙ 10/12/2021

NetRep: Automatic Repair for Network Programs

Debugging imperative network programs is a challenging task for develope...

Lei Shi, et al. ∙

research

∙ 09/24/2021

Few-shot Learning Based on Multi-stage Transfer and Class-Balanced Loss for Diabetic Retinopathy Grading

Diabetic retinopathy (DR) is one of the major blindness-causing diseases...

Lei Shi, et al. ∙

research

∙ 09/24/2021

Dense Contrastive Visual-Linguistic Pretraining

Inspired by the success of BERT, several multimodal representation learn...

Lei Shi, et al. ∙

research

∙ 07/26/2021

Provably Accelerated Decentralized Gradient Method Over Unbalanced Directed Graphs

In this work, we consider the decentralized optimization problem in whic...

Zhuoqing Song, et al. ∙

research

∙ 06/14/2021

Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks

In this paper, we propose two communication-efficient algorithms for dec...

Zhuoqing Song, et al. ∙

research

∙ 06/13/2021

Multi-modal Scene-compliant User Intention Estimation for Navigation

A multi-modal framework to generated user intention distributions when o...

Kavindie Katuwandeniya, et al. ∙

research

∙ 04/26/2021

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

Massive Open Online Courses (MOOCs) have become a popular choice for e-l...

Jialin Yu, et al. ∙

research

∙ 04/06/2021

Inferring Network Structures via Signal Lasso

Inferring the connectivity structure of networked systems from data is a...

Lei Shi, et al. ∙

research

∙ 04/03/2021

A Design Process of Visual Analytics Applications using Conceptual Graph

State-of-the-art visual analytics techniques in application domains are ...

Lei Shi, et al. ∙

research

∙ 03/22/2021

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

Existing methods for skeleton-based action recognition mainly focus on i...

Lei Shi, et al. ∙

research

∙ 10/13/2020

Session-layer Attack Traffic Classification by Program Synthesis

Writing classification rules to identify malicious network traffic is a ...

Lei Shi, et al. ∙

research

∙ 08/18/2020

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

The robust principal component analysis (RPCA) decomposes a data matrix ...

Ningyu Sha, et al. ∙

research

∙ 08/12/2020

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

While Massive Open Online Course (MOOCs) platforms provide knowledge in ...

Ahmed Alamri, et al. ∙

research

∙ 08/12/2020

Revealing the Hidden Patterns: A Comparative Study on Profiling Subpopulations of MOOC Students

Massive Open Online Courses (MOOCs) exhibit a remarkable heterogeneity o...

Lei Shi, et al. ∙

research

∙ 08/12/2020

Validating the Effectiveness of Data-Driven Gamification Recommendations: An Exploratory Study

Gamification design has benefited from data-driven approaches to creatin...

Armando Toda, et al. ∙

research

∙ 08/12/2020

Analysing gamification elements in educational environments using an existing Gamification taxonomy

Gamification has been widely employed in the educational domain over the...

Armando M. Toda, et al. ∙

research

∙ 08/12/2020

Is MOOC Learning Different for Dropouts? A Visually-Driven, Multi-granularity Explanatory ML Approach

Millions of people have enrolled and enrol (especially in the Covid-19 p...

Ahmed Alamri, et al. ∙

research

∙ 08/11/2020

Social Engagement versus Learning Engagement – An Exploratory Study of FutureLearn Learners

Massive Open Online Courses (MOOCs) continue to see increasing enrolment...

Lei Shi, et al. ∙

research

∙ 08/10/2020

Exploring Navigation Styles in a FutureLearn MOOC

This paper presents for the first time a detailed analysis of fine-grain...

Lei Shi, et al. ∙

research

∙ 08/10/2020

Social Interactions Clustering MOOC Students: An Exploratory Study

An exploratory study on social interactions of MOOC students in FutureLe...

Lei Shi, et al. ∙

research

∙ 08/10/2020

Measure the Impact of Institution and Paper via Institution-citation Network

This paper investigates the impact of institutes and papers over time ba...

Xiaomei Bai, et al. ∙

research

∙ 07/26/2020

Contrastive Visual-Linguistic Pretraining

Several multi-modality representation learning approaches such as LXMERT...

Lei Shi, et al. ∙

research

∙ 07/07/2020

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

Dynamic skeletal data, represented as the 2D/3D coordinates of human joi...

Lei Shi, et al. ∙

research

∙ 06/01/2020

Analysis of Least Squares Regularized Regression in Reproducing Kernel Krein Spaces

In this paper, we study the asymptotical properties of least squares reg...

Fanghui Liu, et al. ∙

research

∙ 04/07/2020

SC4D: A Sparse 4D Convolutional Network for Skeleton-Based Action Recognition

In this paper, a new perspective is presented for skeleton-based action ...

Lei Shi, et al. ∙

research

∙ 01/21/2020

Mobility Inference on Long-Tailed Sparse Trajectory

Analyzing the urban trajectory in cities has become an important topic i...

Lei Shi, et al. ∙

research

∙ 12/15/2019

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

Graph convolutional networks (GCNs), which generalize CNNs to more gener...

Lei Shi, et al. ∙

research

∙ 11/28/2019

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

Pose-based action recognition has drawn considerable attention recently....

Lei Shi, et al. ∙

research

∙ 09/17/2019

What Are You Looking at? Detecting Human Intention in Gaze based Human-Robot Interaction

In gaze based Human-Robot Interaction (HRI), it is important to determin...

Lei Shi, et al. ∙

research

∙ 07/18/2019

A study of multivalent q-starlike functions connected with circular domain

In the present article, our aim is to examine some useful problems inclu...

Lei Shi, et al. ∙

research

∙ 07/02/2019

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

Rapidly estimating the remaining wall thickness (RWT) is paramount for t...

Linh Nguyen, et al. ∙

research

∙ 05/22/2019

Planning Gamification Strategies based on User Characteristics and DM: A Gender-based Case Study

Gamification frameworks can aid in gamification planning for education. ...

Armando M. Toda, et al. ∙

research

∙ 04/23/2019

Fine-Grained Named Entity Recognition using ELMo and Wikidata

Fine-grained Named Entity Recognition is a task whereby we detect and cl...

Cihan Dogan, et al. ∙

research

∙ 01/15/2019

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

The prevalence of networked sensors and actuators in many real-world sys...

Dan Li, et al. ∙

research

∙ 01/01/2019

Realizing data features by deep nets

This paper considers the power of deep neural networks (deep nets for sh...

Zheng-Chu Guo, et al. ∙

research

∙ 09/26/2018

Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions

Hyper-kernels endowed by hyper-Reproducing Kernel Hilbert Space (hyper-R...

Fanghui Liu, et al. ∙

research

∙ 09/14/2018

Airdrops and Privacy: A Case Study in Cross-Blockchain Analysis

Airdrops are a popular method of distributing cryptocurrencies and token...

Martin Harrigan, et al. ∙

research

∙ 05/20/2018

Adaptive Spectral Graph Convolutional Networks for Skeleton-Based Action Recognition

Traditional deep methods for skeleton-based action recognition usually s...

Lei Shi, et al. ∙

research

∙ 10/10/2017

Fast and Strong Convergence of Online Learning Algorithms

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

Zheng-Chu Guo, et al. ∙

research

∙ 08/07/2017

Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network

Distributed learning is an effective way to analyze big data. In distrib...

Zhengchu Guo, et al. ∙

research

∙ 03/15/2017

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

Acquiring the accurate 3-D position of a target person around a robot pr...

Mengmeng Wang, et al. ∙

research

∙ 01/03/2017

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

When a measurement falls outside the quantization or measurable range, i...

Xiaolin Huang, et al. ∙

research

∙ 12/01/2016

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

Image pattern recognition is an important area in digital image processi...

Lei Shi, et al. ∙

research

∙ 05/20/2016

Functional Hashing for Compressing Neural Networks

As the complexity of deep neural networks (DNNs) trend to grow to absorb...

Lei Shi, et al. ∙

research

∙ 06/12/2015

Place classification with a graph regularized deep neural network model

Place classification is a fundamental ability that a robot should posses...

Yiyi Liao, et al. ∙

research

∙ 05/14/2015

Pinball Loss Minimization for One-bit Compressive Sensing

The one-bit quantization can be implemented by one single comparator, wh...

Xiaolin Huang, et al. ∙

Lei Shi

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