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Yen-Chang Hsu

According to our database¹, Yen-Chang Hsu authored at least 32 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

On csauthors.net:

Bibliography

2024

Token Fusion: Bridging the Gap between Token Pruning and Token Merging.

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Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters.

[BibT_eX]

[DOI]

James Seale Smith

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CoRR, 2023

Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA.

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[DOI]

James Seale Smith

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CoRR, 2023

Training Energy-Based Normalizing Flow with Score-Matching Objectives.

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

Dynamic Low-rank Estimation for Transformer-based Language Models.

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Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

A Closer Look at Rehearsal-Free Continual Learning.

[BibT_eX]

[DOI]

James Seale Smith

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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Numerical Optimizations for Weighted Low-rank Estimation on Language Model.

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CoRR, 2022

A Closer Look at Rehearsal-Free Continual Learning.

[BibT_eX]

[DOI]

James Seale Smith

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CoRR, 2022

A Closer Look at Knowledge Distillation with Features, Logits, and Gradients.

[BibT_eX]

[DOI]

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James Seale Smith

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CoRR, 2022

DictFormer: Tiny Transformer with Shared Dictionary.

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Proceedings of the Tenth International Conference on Learning Representations, 2022

Language model compression with weighted low-rank factorization.

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Proceedings of the Tenth International Conference on Learning Representations, 2022

Numerical Optimizations for Weighted Low-rank Estimation on Language Models.

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Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Lite-MDETR: A Lightweight Multi-Modal Detector.

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

2021

Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data.

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CoRR, 2021

A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition.

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

Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding.

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[DOI]

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Changsheng Zhao

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Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer.

[BibT_eX]

[DOI]

James Seale Smith

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Jonathan Balloch

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Proceedings of the International Joint Conference on Neural Networks, 2021

Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning.

[BibT_eX]

[DOI]

James Seale Smith

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Jonathan Balloch

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

Enhancing the generalization for Intent Classification and Out-of-Domain Detection in SLU.

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Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Learning from pairwise similarity for visual categorization.

[BibT_eX]

[DOI]

PhD thesis, 2020

Posterior Re-calibration for Imbalanced Datasets.

[BibT_eX]

[DOI]

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Nathaniel Glaser

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Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data.

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

2019

Multi-class classification without multi-class labels.

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Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines.

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CoRR, 2018

A probabilistic constrained clustering for transfer learning and image category discovery.

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CoRR, 2018

Learning to Cluster for Proposal-Free Instance Segmentation.

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Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Learning to cluster in order to transfer across domains and tasks.

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Proceedings of the 6th International Conference on Learning Representations, 2018

Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks.

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Proceedings of the 6th International Conference on Learning Representations, 2018

Training Student Networks for Acceleration with Conditional Adversarial Networks.

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Proceedings of the British Machine Vision Conference 2018, 2018

2017

Learning Loss for Knowledge Distillation with Conditional Adversarial Networks.

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CoRR, 2017

2016

Deep Image Category Discovery using a Transferred Similarity Function.

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CoRR, 2016

2015

Neural network-based clustering using pairwise constraints.

[BibT_eX]

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CoRR, 2015

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