Jingjing Li

A novel genetic algorithm for constructing uniform test forms of cognitive diagnostic models

2016

Cognitive diagnostic models (CDMs) are a new class of test models developed for educational assessment. They have gained growing attention in recent years for their distinctive ability to provide detailed feedback about examinees' ability. Automatic …

KFFM-based Large-scale Project Earned Value Management Completion Prediction

2019 · DEStech Transactions on Engineering and Technology Research

Earned value management lacks research on the project completion trend forecasting method at the following two points: The project completion trend forecast is based on the state indicators at the project monitoring point, and the …

Spectrum Gaussian Processes Based On Tunable Basis Functions

2021 · arXiv (Cornell University)

Spectral approximation and variational inducing learning for the Gaussian process are two popular methods to reduce computational complexity. However, in previous research, those methods always tend to adopt the orthonormal basis functions, such as eigenvectors …

GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning

2022 · IEEE Transactions on Multimedia

Generalized Zero-Shot Learning (GZSL) aims to recognize images not only for seen classes but also for unseen ones by transferring semantic-visual relationships from the seen to the unseen classes. It is an intuitive solution to …

Feature Extraction Method of EEG Signals Evaluating Spatial Cognition of Community Elderly With Permutation Conditional Mutual Information Common Space Model

2023 · IEEE Transactions on Neural Systems and Rehabilitation Engineering

In order to improve the traditional common space pattern (CSP) algorithm pattern in EEG feature extraction, this study proposes a feature extraction method of EEG signals based on permutation conditional mutual information common space pattern …

Order-preserving Consistency Regularization for Domain Adaptation and Generalization

2023

Deep learning models fail on cross-domain challenges if the model is oversensitive to domain-specific attributes, e.g., lightning, background, camera angle, etc. To alleviate this problem, data augmentation coupled with consistency regularization are commonly adopted to …

A Survey on AgentOps: Categorization, Challenges, and Future Directions

2025 · arXiv (Cornell University)

As the reasoning capabilities of Large Language Models (LLMs) continue to advance, LLM-based agent systems offer advantages in flexibility and interpretability over traditional systems, garnering increasing attention. However, despite the widespread research interest and industrial …