Yujia Zheng

Orcid: 0009-0001-6121-0621

According to our database1, Yujia Zheng authored at least 41 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A comprehensive review of deep learning in EEG-based emotion recognition: classifications, trends, and practical implications.
PeerJ Comput. Sci., 2024

Causal-learn: Causal Discovery in Python.
J. Mach. Learn. Res., 2024

A MeanShift-guided oversampling with self-adaptive sizes for imbalanced data classification.
Inf. Sci., 2024

Identifying Selections for Unsupervised Subtask Discovery.
CoRR, 2024

Causality for Large Language Models.
CoRR, 2024

SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks.
CoRR, 2024

Causal Temporal Representation Learning with Nonstationary Sparse Transition.
CoRR, 2024

Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight.
CoRR, 2024

Whole Page Unbiased Learning to Rank.
Proceedings of the ACM on Web Conference 2024, 2024

Source Free Graph Unsupervised Domain Adaptation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Detecting and Identifying Selection Structure in Sequential Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Causal Representation Learning from Multiple Distributions: A General Setting.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Attempts on detecting Alzheimer's disease by fine-tuning pre-trained model with Gaze Data.
Proceedings of the 2024 Symposium on Eye Tracking Research and Applications, 2024

Local Causal Discovery with Linear non-Gaussian Cyclic Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education.
Proceedings of the 26th Australasian Computing Education Conference, 2024

2023
Self-adaptive oversampling method based on the complexity of minority data in imbalanced datasets classification.
Knowl. Based Syst., October, 2023

Partial Identifiability for Domain Adaptation.
CoRR, 2023

Understanding Breast Cancer Survival: Using Causality and Language Models on Multi-omics Data.
CoRR, 2023

Generalizing Nonlinear ICA Beyond Structural Sparsity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Identifiability of Sparse ICA without Assuming Non-Gaussianity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Research on Real-time Early Warning Mechanism of Aviation Safety Based on Finite State Machine Underlying in QAR Stream Data.
Proceedings of the 7th International Conference on Big Data and Internet of Things, 2023

2022
SVDD-based weighted oversampling technique for imbalanced and overlapped dataset learning.
Inf. Sci., 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks.
CoRR, 2022

Whole Page Unbiased Learning to Rank.
CoRR, 2022

Research progress of miRNA-disease association prediction and comparison of related algorithms.
Briefings Bioinform., 2022

MiRNA-disease association prediction based on meta-paths.
Briefings Bioinform., 2022

On the Identifiability of Nonlinear ICA: Sparsity and Beyond.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Partial disentanglement for domain adaptation.
Proceedings of the International Conference on Machine Learning, 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Source Free Unsupervised Graph Domain Adaptation.
CoRR, 2021

Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Elastic Embeddings for Customizing On-Device Recommenders.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Cold-start Sequential Recommendation via Meta Learner.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Heterogeneous Graph Collaborative Filtering.
CoRR, 2020

Long-tail Session-based Recommendation.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

DGTN: Dual-channel Graph Transition Network for Session-based Recommendation.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

2019
Balancing Multi-level Interactions for Session-based Recommendation.
CoRR, 2019

ReFall: Real-Time Fall Detection of Continuous Depth Maps with RFD-Net.
Proceedings of the Image and Graphics Technologies and Applications, 2019


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