Shangling Jui

Orcid: 0000-0002-1047-4264

According to our database1, Shangling Jui authored at least 43 papers between 2019 and 2024.

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Bibliography

2024
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains.
Int. J. Comput. Vis., February, 2024

Rethinking Optimization and Architecture for Tiny Language Models.
CoRR, 2024

A Theory of Non-acyclic Generative Flow Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Trust Your Good Friends: Source-Free Domain Adaptation by Reciprocal Neighborhood Clustering.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Casting a BAIT for offline and online source-free domain adaptation.
Comput. Vis. Image Underst., September, 2023

Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Models.
CoRR, 2023

A Theory of Non-Acyclic Generative Flow Networks.
CoRR, 2023

Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering.
CoRR, 2023

Ternary Singular Value Decomposition as a Better Parameterized Form in Linear Mapping.
CoRR, 2023

Reparameterization through Spatial Gradient Scaling.
CoRR, 2023

A General-Purpose Transferable Predictor for Neural Architecture Search.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Exploring the Training Robustness of Distributional Reinforcement Learning Against Noisy State Observations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

AutoGO: Automated Computation Graph Optimization for Neural Network Evolution.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reparameterization through Spatial Gradient Scaling.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

AIO-P: Expanding Neural Performance Predictors beyond Image Classification.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

GENNAPE: Towards Generalized Neural Architecture Performance Estimators.
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.
CoRR, 2022

A Memory-Bounded Best-First Beam Search and Its Application to Scheduling Halide Programs.
Proceedings of the Fifteenth International Symposium on Combinatorial Search, 2022

Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation.
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.
Proceedings of the Tenth International Conference on Learning Representations, 2022

R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition.
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.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability.
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.
CoRR, 2021

Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations.
CoRR, 2021

MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains.
CoRR, 2021

Exploring Neural Architecture Search Space via Deep Deterministic Sampling.
IEEE Access, 2021

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation.
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.
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.
Proceedings of the IEEE International Test Conference, 2021

Generative Adversarial Neural Architecture Search.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Bansor: Improving Tensor Program Auto-Scheduling with Bandit Based Reinforcement Learning.
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Generalized Source-free Domain Adaptation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

ReNAS: Relativistic Evaluation of Neural Architecture Search.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search.
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.
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.
CoRR, 2020

Neural Architecture Search for Keyword Spotting.
Proceedings of the Interspeech 2020, 2020

Generative Feature Replay For Class-Incremental Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Semantic Drift Compensation for Class-Incremental Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
RNAS: Architecture Ranking for Powerful Networks.
CoRR, 2019

Deep Demosaicing for Edge Implementation.
Proceedings of the Image Analysis and Recognition - 16th International Conference, 2019


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