Lei Zhang

Attribute-Aware Graph Recurrent Networks for Scholarly Friend Recommendation Based on Internet of Scholars in Scholarly Big Data

2020 · IEEE Transactions on Industrial Informatics

The academic society is stepping into the age of scholarly big data, where finding suitable scholars for collaboration has become ever difficult. Scholarly recommendation approaches are designed to overcome the information overload problems. However, previous …

Improved square root adaptive cubature Kalman filter

2019 · IET Signal Processing

In this study, an improved square root adaptive cubature Kalman filter (ISRACKF) is proposed to improve the filter performance in terms of accuracy, computation efficiency, and robustness. Through the evaluated measure of non‐linearity value, the …

Knowledge-Based Short Text Categorization Using Entity and Category Embedding

2019 · Lecture notes in computer science

Short text categorization is an important task due to the rapid growth of online available short texts in various domains such as web search snippets, etc. Most of the traditional methods suffer from sparsity and …

Summary of Association Rules

2019 · IOP Conference Series Earth and Environmental Science

In recent years, scholars at home and abroad have conducted a large number of researches on association rules, in order to deeply understand the mining technology of association rules, and master its research status and …

Personalized exercise recommendation via implicit skills

2019 · Proceedings of the ACM Turing Celebration Conference - China

Cognitive diagnosis methods need to assess the students' skills to provide personalized exercise recommendation. To perform this assessment, an initially hand built Q-matrix are presented to students, which would affect the recommendation results in intelligence …

Discrete Intelligible Recognition Network

2020

We present a new approach to recognize object and we test it in MNIST data set. The main purpose of this method is to solve some problems encountered by most current artificial intelligence. Firstly, most …

Research on Visualization Algorithm of Association Rules Based on Concept Lattice

2020

The traditional association rule representation method has no way to show the essential relationship between concepts and lacks understanding of the concept level. Concept lattice is a kind of data structure which can show the …

Dynamic Weighted Learning for Unsupervised Domain Adaptation

2021 · arXiv (Cornell University)

Unsupervised domain adaptation (UDA) aims to improve the classification performance on an unlabeled target domain by leveraging information from a fully labeled source domain. Recent approaches explore domain-invariant and class-discriminant representations to tackle this task. …

Using a Novel Algorithm Based on the Random Vector Functional Link Network and Multi-Verse Optimizer to Forecast Effluent Quality

2022 · Sustainability

The treatment of wastewater is a complicated biological reaction process. Reliable effluent prediction is critical in the scientific management of water treatment plants. This research proposes a soft sensor design strategy to address the issues …

Few-shot Multi-hop Question Answering over Knowledge Base

2021 · arXiv (Cornell University)

KBQA is a task that requires to answer questions by using semantic structured information in knowledge base. Previous work in this area has been restricted due to the lack of large semantic parsing dataset and …

Construction and Adjustment Methods for Teacher-Student Relationship in College Student Management Based on Big Data Analysis

2022 · International Journal of Emerging Technologies in Learning (iJET)

Building a harmonious Teacher-Student Relationship (TSR) is a necessary work for college student management, because different TSRs can result in different effects in student management and cultivation. However, in existing studies, the definitions of harmonious …

A Privacy-Preserving Blockchain Platform for a Data Marketplace

2022 · Distributed Ledger Technologies Research and Practice

Recent data leak scandals, together with the under-utilization of collected data (estimated that around 90% of data never leaves a device’s local storage), limits the applicability and potential of novel data driven applications. Thus, novel …

Evaluation method of online education quality based on Fuzzy Rough Set

2023 · International Journal of Continuing Engineering Education and Life-Long Learning

In order to overcome the problems of unreasonable index weight distribution, poor quality evaluation results and low accuracy in the process of online education quality evaluation, this paper proposes a method of online education quality …

Multi-View Clustering from the Perspective of Mutual Information

2023 · arXiv (Cornell University)

Exploring the complementary information of multi-view data to improve clustering effects is a crucial issue in multi-view clustering. In this paper, we propose a novel model based on information theory termed Informative Multi-View Clustering (IMVC), …

A smart contract vulnerability detection model based on graph neural networks

2022

In recent years, smart contract vulnerability detection methods mostly view smart contract source code as natural language for processing, which cannot fully capture the semantic and structural features of the source code and has a …

Deep Reinforcement Learning for Two-Player DouDizhu

2022

Recently, DouZero, an AI system for the game of DouDizhu, has been proposed and made a breakthrough by reaching human level in DouDizhu, one of the most popular imperfect information games in China. In order …

LipsFormer: Introducing Lipschitz Continuity to Vision Transformers

2023 · arXiv (Cornell University)

We present a Lipschitz continuous Transformer, called LipsFormer, to pursue training stability both theoretically and empirically for Transformer-based models. In contrast to previous practical tricks that address training instability by learning rate warmup, layer normalization, …

DRGCN: Dynamic Evolving Initial Residual for Deep Graph Convolutional Networks

2023 · Proceedings of the AAAI Conference on Artificial Intelligence

Graph convolutional networks (GCNs) have been proved to be very practical to handle various graph-related tasks. It has attracted considerable research interest to study deep GCNs, due to their potential superior performance compared with shallow …

Online Federated Learning for Air-Ground Edge Intelligence

2023

Traditional federated learning (FL) usually relies on static ground base stations (BSs) for model aggregation. Unmanned aerial vehicles (UAVs), due to their flexible 3D deployment, can effectively complement ground BSs, enabling the establishment of air-ground …

Quantum evolution speed and its limit in the driven double‐well system

2023 · International Journal of Quantum Chemistry

Abstract We investigate quantum evolution speed in the driven double‐well system using the entangled trajectory molecular dynamics method. We emphasize not only the evolution speed of the quantum state but also its limit according to …

An Efficient VHDL Implementation of two Artificial Neural Networks on Zynq-7000 FPGA

2023

This paper presents the FPGA implementation of two different topologies of an Artificial Neural Network (ANN) on the Xilinx Zynq-7000 evaluation board. The engine dataset available in MATLAB is used to train the neural network. …

Grammatical Evolution for Predicting Cervical Cancer Recurrence Risk

2023

Cervical cancer is one of the most common tumors in women and has a high rate of recurrence after surgery. Early detection of symptoms leading to earlier treatment can significantly reduce the risk of patients. …

A Named Entity Recognition Method Based on Knowledge Distillation and Efficient GlobalPointer for Chinese Medical Texts

2024 · IEEE Access

The task of named entity recognition has been widely used in medical text analysis, but there is still the problem of poor transfer ability in practical applications. This work proposes a novel named entity recognition …

YuLan: An Open-source Large Language Model

2024 · arXiv (Cornell University)

Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many open-source LLMs have been released with technical reports, the lack of training …

A Method for Predicting the Impact of Labor Education at Institutions of Higher Education Based on a Two-Stage Clustering Algorithm

2024 · International Journal of High Speed Electronics and Systems

In order to develop more accurate teaching plans and methods based on students’ characteristics and needs, and improve the effectiveness of labor education, a two-stage clustering algorithm based method for predicting the effectiveness of labor …

Soft-Error Analysis of RRAM 1T1R Compute-In-Memory Core for Artificial Neural Networks

2024

This work analyses SEU-induced soft-errors in analog compute-in-memory cores using resistive random-access memory (RRAM) for artificial neural networks, where their bitcells utilize one-transistor-one-RRAM (1T1R) structure. This is modeled by combining the Stanford-PKU RRAM Model and …

Imitate Before Detect: Aligning Machine Stylistic Preference for Machine-Revised Text Detection

2024 · arXiv (Cornell University)

Large Language Models (LLMs) have revolutionized text generation, making detecting machine-generated text increasingly challenging. Although past methods have achieved good performance on detecting pure machine-generated text, those detectors have poor performance on distinguishing machine-revised text …

The Comp-TSSs Scheme for Anomaly Detection in AI-Powered Autonomous Driving

2025 · ACM Transactions on Autonomous and Adaptive Systems

Given the vulnerability of vehicular networks to security attacks and the criticality of secure AI-powered autonomous driving, this paper emphasizes the security issue concerning vehicular networks in AI-powered autonomous vehicles. The novel complementary tensor summary …

Generalizable Retrieve-Based Method for Task Oriented Dialogue State Tracking

2025

Dialogue state tracking(DST) is an essential component of task oriented dialogue(TOD) system. Recent research in schema guided DST utilizing semantic information offered by schema has seen great progress in transferring to new unseen domains. However, …

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation

2025 · arXiv (Cornell University)

Ads recommendation is a prominent service of online advertising systems and has been actively studied. Recent studies indicate that scaling-up and advanced design of the recommendation model can bring significant performance improvement. However, with a …

Resolution-Induced Collapse in Quantized Nonlinear Dynamics: A Finite-Horizon Structural Framework

2026 · Electronics

Finite-precision implementation fundamentally changes nonlinear dynamical systems by replacing continuous-state evolution with deterministic dynamics on a finite set of representable states. This study examines when that change becomes structurally important over a finite observation horizon. …

A Survey of Collaborative Filtering-Based Recommender Systems: From Traditional Methods to Hybrid Methods Based on Social Networks

2018 · IEEE Access

In the era of big data, recommender system (RS) has become an effective information filtering tool that alleviates information overload for Web users. Collaborative filtering (CF), as one of the most successful recommendation techniques, has …