We stand with Ukraine

We stand with Ukraine

Zhi-Lin Zhao

Orcid: 0000-0001-6391-8423

Affiliations:

University of Technology Sydney, Data Science Lab, NSW, Australia
Sun Yat-sen University, School of Data and Computer Science, Guangzhou, China (former)

According to our database¹, Zhi-Lin Zhao authored at least 22 papers between 2015 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

Online presence:

on orcid.org

On csauthors.net:

Bibliography

2024

Rethinking CLIP-based Video Learners in Cross-Domain Open-Vocabulary Action Recognition.

[BibT_eX]

[DOI]

,

,

,

,

,

Chen Change Loy

,

CoRR, 2024

2023

Supervision Adaptation Balancing In-Distribution Generalization and Out-of-Distribution Detection.

[BibT_eX]

[DOI]

,

,

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Revealing the Distributional Vulnerability of Discriminators by Implicit Generators.

[BibT_eX]

[DOI]

,

,

IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Out-of-Distribution Knowledge Distillation via Confidence Amendment.

[BibT_eX]

[DOI]

,

,

CoRR, 2023

R-divergence for Estimating Model-oriented Distribution Discrepancy.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Spectral Copula Mechanisms Modeling Coupled and Volatile Multivariate Time Series.

[BibT_eX]

[DOI]

,

,

Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

2022

Label and Distribution-discriminative Dual Representation Learning for Out-of-Distribution Detection.

[BibT_eX]

[DOI]

,

CoRR, 2022

Out-of-distribution Detection by Cross-class Vicinity Distribution of In-distribution Data.

[BibT_eX]

[DOI]

,

,

CoRR, 2022

Supervision Adaptation Balances In-Distribution Generalization and Out-of-Distribution Detection.

[BibT_eX]

[DOI]

,

,

CoRR, 2022

Gray Learning from Non-IID Data with Out-of-distribution Samples.

[BibT_eX]

[DOI]

,

,

Chang-Dong Wang

CoRR, 2022

Coupling Online-Offline Learning for Multi-distributional Data Streams.

[BibT_eX]

[DOI]

,

,

CoRR, 2022

Shallow and Deep Non-IID Learning on Complex Data.

[BibT_eX]

[DOI]

,

,

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Revealing Distributional Vulnerability of Explicit Discriminators by Implicit Generators.

[BibT_eX]

[DOI]

,

,

CoRR, 2021

2019

LSCD: Low-rank and sparse cross-domain recommendation.

[BibT_eX]

[DOI]

,

,

Chang-Dong Wang

,

,

Neurocomputing, 2019

2018

Low-Rank and Sparse Cross-Domain Recommendation Algorithm.

[BibT_eX]

[DOI]

,

,

Chang-Dong Wang

,

Proceedings of the Database Systems for Advanced Applications, 2018

2017

An item orientated recommendation algorithm from the multi-view perspective.

[BibT_eX]

[DOI]

,

,

Chang-Dong Wang

,

Neurocomputing, 2017

Recommendation in feature space sphere.

[BibT_eX]

[DOI]

,

Chang-Dong Wang

,

,

Electron. Commer. Res. Appl., 2017

Multi-view Unit Intact Space Learning.

[BibT_eX]

[DOI]

,

Chang-Dong Wang

,

,

Proceedings of the Knowledge Science, Engineering and Management, 2017

Low-Rank and Sparse Matrix Completion for Recommendation.

[BibT_eX]

[DOI]

,

,

Chang-Dong Wang

,

,

Proceedings of the Neural Information Processing - 24th International Conference, 2017

Missing Value Learning.

[BibT_eX]

[DOI]

,

Chang-Dong Wang

,

,

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016

FTMF: Recommendation in social network with Feature Transfer and Probabilistic Matrix Factorization.

[BibT_eX]

[DOI]

,

Chang-Dong Wang

,

,

,

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

Pipeline Item-Based Collaborative Filtering Based on MapReduce.

[BibT_eX]

[DOI]

,

Chang-Dong Wang

,

,

,

Proceedings of the Fifth IEEE International Conference on Big Data and Cloud Computing, 2015

Loading...