Long-Kai Huang

Orcid: 0000-0001-5263-1443

According to our database1, Long-Kai Huang authored at least 25 papers between 2013 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Invariant Test-Time Adaptation for Vision-Language Model Generalization.
CoRR, 2024

2023
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation.
IEEE Trans. Knowl. Data Eng., December, 2023

Deep domain adversarial neural network for the deconvolution of cell type mixtures in tissue proteome profiling.
Nat. Mac. Intell., October, 2023

Retaining Beneficial Information from Detrimental Data for Neural Network Repair.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Secure Out-of-Distribution Task Generalization with Energy-Based Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Concept-wise Fine-tuning Matters in Preventing Negative Transfer.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery?
CoRR, 2022

Learning to generate imaginary tasks for improving generalization in meta-learning.
CoRR, 2022

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations.
CoRR, 2022

Adversarial Task Up-sampling for Meta-learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Frustratingly Easy Transferability Estimation.
Proceedings of the International Conference on Machine Learning, 2022

2021
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improving Generalization in Meta-learning via Task Augmentation.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Advanced topics in learning to hash for large-scale retrieval
PhD thesis, 2020

Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning.
CoRR, 2020

Communication-Efficient Distributed PCA by Riemannian Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
A fast online spherical hashing method based on data sampling for large scale image retrieval.
Neurocomputing, 2019

Accelerate Learning of Deep Hashing With Gradient Attention.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Online Hashing.
IEEE Trans. Neural Networks Learn. Syst., 2018

Recurrent knowledge graph embedding for effective recommendation.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

2016
Class-Wise Supervised Hashing with Label Embedding and Active Bits.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2013
Smart Hashing Update for Fast Response.
Proceedings of the IJCAI 2013, 2013


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