Jiangchao Yao

Orcid: 0000-0001-6115-5194

According to our database1, Jiangchao Yao authored at least 91 papers between 2015 and 2024.

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

Timeline

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Bibliography

2024
UniChest: Conquer-and-Divide Pre-Training for Multi-Source Chest X-Ray Classification.
IEEE Trans. Medical Imaging, August, 2024

Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems.
IEEE Trans. Knowl. Data Eng., February, 2024

Server-Client Collaborative Distillation for Federated Reinforcement Learning.
ACM Trans. Knowl. Discov. Data, January, 2024

Balanced Destruction-Reconstruction Dynamics for Memory-Replay Class Incremental Learning.
IEEE Trans. Image Process., 2024

LoRKD: Low-Rank Knowledge Decomposition for Medical Foundation Models.
CoRR, 2024

Knowledge-Enhanced Facial Expression Recognition with Emotional-to-Neutral Transformation.
CoRR, 2024

Decoupling the Class Label and the Target Concept in Machine Unlearning.
CoRR, 2024

Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping.
CoRR, 2024

Mitigating Label Noise on Graph via Topological Sample Selection.
CoRR, 2024

Enhancing Cross-Domain Click-Through Rate Prediction via Explicit Feature Augmentation.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Reprogramming Distillation for Medical Foundation Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mitigating Label Noise on Graphs via Topological Sample Selection.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Diversified Batch Selection for Training Acceleration.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

MVTexGen: Synthesising 3D Textures Using Multi-View Diffusion.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Long-tailed Diffusion Models with Oriented Calibration.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

On Harmonizing Implicit Subpopulations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Pre-Post Interaction Learning for Brain Tumor Segmentation with Missing MRI Modalities.
Proceedings of the IEEE International Conference on Acoustics, 2024

ReMamber: Referring Image Segmentation with Mamba Twister.
Proceedings of the Computer Vision - ECCV 2024, 2024

Low-Rank Knowledge Decomposition for Medical Foundation Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Latent Class-Conditional Noise Model.
IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI.
IEEE Trans. Knowl. Data Eng., July, 2023

Contrastive Attraction and Contrastive Repulsion for Representation Learning.
Trans. Mach. Learn. Res., 2023

Federated Learning under Partially Disjoint Data via Manifold Reshaping.
Trans. Mach. Learn. Res., 2023

CogKR: Cognitive Graph for Multi-Hop Knowledge Reasoning.
IEEE Trans. Knowl. Data Eng., 2023

DeepInception: Hypnotize Large Language Model to Be Jailbreaker.
CoRR, 2023

Long-Range Neural Atom Learning for Molecular Graphs.
CoRR, 2023

Combating Bilateral Edge Noise for Robust Link Prediction.
CoRR, 2023

Redundancy-Adaptive Multimodal Learning for Imperfect Data.
CoRR, 2023

Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation.
CoRR, 2023

UniBrain: Universal Brain MRI Diagnosis with Hierarchical Knowledge-enhanced Pre-training.
CoRR, 2023

Bag of Tricks for Long-Tailed Multi-Label Classification on Chest X-Rays.
CoRR, 2023

Towards Efficient Task-Driven Model Reprogramming with Foundation Models.
CoRR, 2023

Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Combating Bilateral Edge Noise for Robust Link Prediction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Federated Learning with Bilateral Curation for Partially Class-Disjoint Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Combating Representation Learning Disparity with Geometric Harmonization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GRACE: A Generalized and Personalized Federated Learning Method for Medical Imaging.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability.
Proceedings of the International Conference on Machine Learning, 2023

Exploring Model Dynamics for Accumulative Poisoning Discovery.
Proceedings of the International Conference on Machine Learning, 2023

On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation.
Proceedings of the International Conference on Machine Learning, 2023

Combating Exacerbated Heterogeneity for Robust Models in Federated Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Long-Tailed Partial Label Learning via Dynamic Rebalancing.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Federated Domain Generalization with Generalization Adjustment.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Class-Balancing Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Zero-shot Composed Text-Image Retrieval.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Learning on Attribute-Missing Graphs.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Device-cloud Collaborative Recommendation via Meta Controller.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Contrastive Learning with Boosted Memorization.
Proceedings of the International Conference on Machine Learning, 2022

Reliable Adversarial Distillation with Unreliable Teachers.
Proceedings of the Tenth International Conference on Learning Representations, 2022

FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation.
Proceedings of the IEEE International Conference on Data Mining, 2022

PEAR: Photographic Embedding for Aesthetic Rating.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Decoupled Variational Embedding for Signed Directed Networks.
ACM Trans. Web, 2021

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey.
CoRR, 2021

Click-through Rate Prediction with Auto-Quantized Contrastive Learning.
CoRR, 2021

MC$^2$-SF: Slow-Fast Learning for Mobile-Cloud Collaborative Recommendation.
CoRR, 2021

Contrastive Conditional Transport for Representation Learning.
CoRR, 2021

Sparse-Interest Network for Sequential Recommendation.
Proceedings of the WSDM '21, 2021

Device-Cloud Collaborative Learning for Recommendation.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Cooperative Learning for Noisy Supervision.
Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Learning with Group Noise.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
Deep learning with noisy supervision
PhD thesis, 2019

Deep Learning From Noisy Image Labels With Quality Embedding.
IEEE Trans. Image Process., 2019

Node Attribute Generation on Graphs.
CoRR, 2019

How does Disagreement Help Generalization against Label Corruption?
Proceedings of the 36th International Conference on Machine Learning, 2019

Collaborative Label Correction via Entropy Thresholding.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Bayes EMbedding (BEM): Refining Representation by Integrating Knowledge Graphs and Behavior-specific Networks.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Understanding VAEs in Fisher-Shannon Plane.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Safeguarded Dynamic Label Regression for Noisy Supervision.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Joint Latent Dirichlet Allocation for Social Tags.
IEEE Trans. Multim., 2018

Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels.
CoRR, 2018

Variational Collaborative Learning for User Probabilistic Representation.
CoRR, 2018

Understanding VAEs in Fisher-Shannon Plane.
CoRR, 2018

Variational Composite Autoencoders.
CoRR, 2018

Degeneration in VAE: in the Light of Fisher Information Loss.
CoRR, 2018

Masking: A New Perspective of Noisy Supervision.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Collaborative Learning for Weakly Supervised Object Detection.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Recommendation with Hybrid Interest Model.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

2017
Describing Geographical Characteristics with Social Images.
Proceedings of the MultiMedia Modeling - 23rd International Conference, 2017

Discovering User Interests from Social Images.
Proceedings of the MultiMedia Modeling - 23rd International Conference, 2017

2016
Preference Aware Recommendation Based on Categorical Information.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

2015
Online Learning Algorithm for Collective LDA.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

Joint Latent Dirichlet Allocation for non-iid social tags.
Proceedings of the 2015 IEEE International Conference on Multimedia and Expo, 2015


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