Shangling Jui

According to our database, Shangling Jui authored at least 44 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains.

Yaxing Wang, Abel Gonzalez-Garcia, Chenshen Wu, Luis Herranz, Fahad Shahbaz Khan, Shangling Jui, Jian Yang, Joost van de Weijer

Int. J. Comput. Vis., February, 2024

LMM-VQA: Advancing Video Quality Assessment with Large Multimodal Models.

Qihang Ge, Wei Sun, Yu Zhang, Yunhao Li, Zhongpeng Ji, Fengyu Sun, Shangling Jui, Xiongkuo Min, Guangtao Zhai

CoRR, 2024

Benchmarking AIGC Video Quality Assessment: A Dataset and Unified Model.

Zhichao Zhang, Xinyue Li, Wei Sun, Jun Jia, Xiongkuo Min, Zicheng Zhang, Chunyi Li, Zijian Chen, Puyi Wang, Zhongpeng Ji, Fengyu Sun, Shangling Jui, Guangtao Zhai

CoRR, 2024

Rethinking Optimization and Architecture for Tiny Language Models.

Yehui Tang, Kai Han, Fangcheng Liu, Yunsheng Ni, Yuchuan Tian, Zheyuan Bai, Yi-Qi Hu, Sichao Liu, Shangling Jui, Yunhe Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Q-Boost: On Visual Quality Assessment Ability of Low-Level Multi-Modality Foundation Models.

Zicheng Zhang, Haoning Wu, Zhongpeng Ji, Chunyi Li, Erli Zhang, Wei Sun, Xiaohong Liu, Xiongkuo Min, Fengyu Sun, Shangling Jui, Weisi Lin, Guangtao Zhai

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

A Theory of Non-acyclic Generative Flow Networks.

Leo Maxime Brunswic, Yinchuan Li, Yushun Xu, Yijun Feng, Shangling Jui, Lizhuang Ma

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Trust Your Good Friends: Source-Free Domain Adaptation by Reciprocal Neighborhood Clustering.

Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui, Jian Yang

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

Casting a BAIT for offline and online source-free domain adaptation.

Shiqi Yang, Yaxing Wang, Luis Herranz, Shangling Jui, Joost van de Weijer

Comput. Vis. Image Underst., September, 2023

A Theory of Non-Acyclic Generative Flow Networks.

Leo Maxime Brunswic, Yinchuan Li, Yushun Xu, Shangling Jui, Lizhuang Ma

CoRR, 2023

Ternary Singular Value Decomposition as a Better Parameterized Form in Linear Mapping.

Boyu Chen, Hanxuan Chen, Jiao He, Fengyu Sun, Shangling Jui

CoRR, 2023

Reparameterization through Spatial Gradient Scaling.

Alexander Detkov, Mohammad Salameh, Muhammad Fetrat Qharabagh, Jialin Zhang, Wei Lui, Shangling Jui, Di Niu

CoRR, 2023

A General-Purpose Transferable Predictor for Neural Architecture Search.

Fred X. Han, Keith G. Mills, Fabian Chudak, Parsa Riahi, Mohammad Salameh, Jialin Zhang, Wei Lu, Shangling Jui, Di Niu

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Exploring the Training Robustness of Distributional Reinforcement Learning Against Noisy State Observations.

Ke Sun, Yingnan Zhao, Shangling Jui, Linglong Kong

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

AutoGO: Automated Computation Graph Optimization for Neural Network Evolution.

Mohammad Salameh, Keith G. Mills, Negar Hassanpour, Fred X. Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun, Di Niu

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

Reparameterization through Spatial Gradient Scaling.

Alexander Detkov, Mohammad Salameh, Muhammad Fetrat Qharabagh, Jialin Zhang, Robin Luwei, Shangling Jui, Di Niu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

AIO-P: Expanding Neural Performance Predictors beyond Image Classification.

Keith G. Mills, Di Niu, Mohammad Salameh, Weichen Qiu, Fred X. Han, Puyuan Liu, Jialin Zhang, Wei Lu, Shangling Jui

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

GENNAPE: Towards Generalized Neural Architecture Performance Estimators.

Keith G. Mills, Fred X. Han, Jialin Zhang, Fabian Chudak, Ali Safari Mamaghani, Mohammad Salameh, Wei Lu, Shangling Jui, Di Niu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

One Ring to Bring Them All: Towards Open-Set Recognition under Domain Shift.

Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost van de Weijer

CoRR, 2022

A Memory-Bounded Best-First Beam Search and Its Application to Scheduling Halide Programs.

Chao Gao, Jingwei Chen, Tong Mo, Tanvir Sajed, Shangling Jui, Min Qin, Laiyuan Gong, Wei Lu

Proceedings of the Fifteenth International Symposium on Combinatorial Search, 2022

Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation.

Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost van de Weijer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Distilling GANs with Style-Mixed Triplets for X2I Translation with Limited Data.

Yaxing Wang, Joost van de Weijer, Lu Yu, Shangling Jui

Proceedings of the Tenth International Conference on Learning Representations, 2022

R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning.

Shengyao Lu, Bang Liu, Keith G. Mills, Shangling Jui, Di Niu

Proceedings of the Tenth International Conference on Learning Representations, 2022

Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition.

Kai Wang, Xialei Liu, Andy Bagdanov, Luis Herranz, Shangling Jui, Joost van de Weijer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification.

Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost van de Weijer

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability.

Yafei Wang, Bo Pan, Wei Tu, Peng Liu, Bei Jiang, Chao Gao, Wei Lu, Shangling Jui, Linglong Kong

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.

Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

CoRR, 2021

Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations.

Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, Linglong Kong

CoRR, 2021

MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains.

Yaxing Wang, Abel Gonzalez-Garcia, Chenshen Wu, Luis Herranz, Fahad Shahbaz Khan, Shangling Jui, Joost van de Weijer

CoRR, 2021

Exploring Neural Architecture Search Space via Deep Deterministic Sampling.

Keith G. Mills, Mohammad Salameh, Di Niu, Fred X. Han, Seyed Saeed Changiz Rezaei, Hengshuai Yao, Wei Lu, Shuo Lian, Shangling Jui

IEEE Access, 2021

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation.

Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization.

Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adaptive NN-based Root Cause Analysis in Volume Diagnosis for Yield Improvement.

Xin Huang, Min Qin, Ruosheng Xu, Cheng Chen, Shangling Jui, Zhihao Ding, Pengyun Li, Yu Huang

Proceedings of the IEEE International Test Conference, 2021

Generative Adversarial Neural Architecture Search.

Seyed Saeed Changiz Rezaei, Fred X. Han, Di Niu, Mohammad Salameh, Keith G. Mills, Shuo Lian, Wei Lu, Shangling Jui

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Bansor: Improving Tensor Program Auto-Scheduling with Bandit Based Reinforcement Learning.

Chao Gao, Tong Mo, Taylor Zowtuk, Tanvir Sajed, Laiyuan Gong, Hanxuan Chen, Shangling Jui, Wei Lu

Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Generalized Source-free Domain Adaptation.

Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

ReNAS: Relativistic Evaluation of Neural Architecture Search.

Yixing Xu, Yunhe Wang, Kai Han, Yehui Tang, Shangling Jui, Chunjing Xu, Chang Xu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search.

Keith G. Mills, Fred X. Han, Jialin Zhang, Seyed Saeed Changiz Rezaei, Fabian Chudak, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

L2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.

Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Unsupervised Domain Adaptation without Source Data by Casting a BAIT.

Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui

CoRR, 2020

Neural Architecture Search for Keyword Spotting.

Tong Mo, Yakun Yu, Mohammad Salameh, Di Niu, Shangling Jui

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Generative Feature Replay For Class-Incremental Learning.

Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Semantic Drift Compensation for Class-Incremental Learning.

Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

RNAS: Architecture Ranking for Powerful Networks.

Yixing Xu, Yunhe Wang, Kai Han, Hanting Chen, Yehui Tang, Shangling Jui, Chunjing Xu, Qi Tian, Chang Xu

CoRR, 2019

Deep Demosaicing for Edge Implementation.

Ramchalam Kinattinkara Ramakrishnan, Shangling Jui, Vahid Partovi Nia

Proceedings of the Image Analysis and Recognition - 16th International Conference, 2019