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2020 – today
- 2024
[j1]James Seale Smith, Yen-Chang Hsu, Lingyu Zhang, Ting Hua, Zsolt Kira, Yilin Shen, Hongxia Jin:
Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA. Trans. Mach. Learn. Res. 2024 (2024)- [c24]James Seale Smith, Yen-Chang Hsu, Zsolt Kira, Yilin Shen, Hongxia Jin:
Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters. CVPR Workshops 2024: 1744-1754 - [c23]Shangqian Gao, Ting Hua, Yen-Chang Hsu, Yilin Shen, Hongxia Jin:
Adaptive Rank Selections for Low-Rank Approximation of Language Models. NAACL-HLT 2024: 227-241 - [c22]Chi-Heng Lin, Shikhar Tuli, James Seale Smith, Yen-Chang Hsu, Yilin Shen, Hongxia Jin:
SLiM: Speculative Decoding with Hypothesis Reduction. NAACL-HLT (Findings) 2024: 1005-1017 - [c21]Shikhar Tuli, Chi-Heng Lin, Yen-Chang Hsu, Niraj K. Jha, Yilin Shen, Hongxia Jin:
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling. NAACL-HLT 2024: 3322-3345 - [c20]Minchul Kim, Shangqian Gao, Yen-Chang Hsu, Yilin Shen, Hongxia Jin:
Token Fusion: Bridging the Gap between Token Pruning and Token Merging. WACV 2024: 1372-1381 - [i26]Shikhar Tuli, Chi-Heng Lin, Yen-Chang Hsu, Niraj K. Jha, Yilin Shen, Hongxia Jin:
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling. CoRR abs/2405.00888 (2024) - [i25]Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu:
MoDeGPT: Modular Decomposition for Large Language Model Compression. CoRR abs/2408.09632 (2024) - 2023
- [c19]James Seale Smith, Junjiao Tian, Shaunak Halbe, Yen-Chang Hsu, Zsolt Kira:
A Closer Look at Rehearsal-Free Continual Learning. CVPR Workshops 2023: 2410-2420 - [c18]Ting Hua, Xiao Li, Shangqian Gao, Yen-Chang Hsu, Yilin Shen, Hongxia Jin:
Dynamic Low-rank Estimation for Transformer-based Language Models. EMNLP (Findings) 2023: 9275-9287 - [c17]Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee:
Training Energy-Based Normalizing Flow with Score-Matching Objectives. NeurIPS 2023 - [i24]James Seale Smith, Yen-Chang Hsu, Lingyu Zhang, Ting Hua, Zsolt Kira, Yilin Shen, Hongxia Jin:
Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA. CoRR abs/2304.06027 (2023) - [i23]Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee:
Training Energy-Based Normalizing Flow with Score-Matching Objectives. CoRR abs/2305.15267 (2023) - [i22]James Seale Smith, Yen-Chang Hsu, Zsolt Kira, Yilin Shen, Hongxia Jin:
Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters. CoRR abs/2311.18763 (2023) - [i21]Minchul Kim
, Shangqian Gao, Yen-Chang Hsu, Yilin Shen, Hongxia Jin:
Token Fusion: Bridging the Gap between Token Pruning and Token Merging. CoRR abs/2312.01026 (2023) - 2022
- [c16]Qian Lou, Yen-Chang Hsu, Burak Uzkent, Ting Hua, Yilin Shen, Hongxia Jin:
Lite-MDETR: A Lightweight Multi-Modal Detector. CVPR 2022: 12196-12205 - [c15]Ting Hua, Yen-Chang Hsu, Felicity Wang, Qian Lou, Yilin Shen, Hongxia Jin:
Numerical Optimizations for Weighted Low-rank Estimation on Language Models. EMNLP 2022: 1404-1416 - [c14]Yen-Chang Hsu, Ting Hua, Sungen Chang, Qian Lou, Yilin Shen, Hongxia Jin:
Language model compression with weighted low-rank factorization. ICLR 2022 - [c13]Qian Lou, Ting Hua, Yen-Chang Hsu, Yilin Shen, Hongxia Jin:
DictFormer: Tiny Transformer with Shared Dictionary. ICLR 2022 - [i20]Ting Hua, Yilin Shen, Changsheng Zhao, Yen-Chang Hsu, Hongxia Jin:
Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding. CoRR abs/2201.01420 (2022) - [i19]Yen-Chang Hsu, James Seale Smith, Yilin Shen, Zsolt Kira, Hongxia Jin:
A Closer Look at Knowledge Distillation with Features, Logits, and Gradients. CoRR abs/2203.10163 (2022) - [i18]James Seale Smith, Junjiao Tian, Yen-Chang Hsu, Zsolt Kira:
A Closer Look at Rehearsal-Free Continual Learning. CoRR abs/2203.17269 (2022) - [i17]Yen-Chang Hsu, Ting Hua, Sungen Chang, Qian Lou, Yilin Shen, Hongxia Jin:
Language model compression with weighted low-rank factorization. CoRR abs/2207.00112 (2022) - [i16]Ting Hua, Yen-Chang Hsu, Felicity Wang, Qian Lou, Yilin Shen, Hongxia Jin:
Numerical Optimizations for Weighted Low-rank Estimation on Language Model. CoRR abs/2211.09718 (2022) - 2021
- [c12]Yilin Shen, Yen-Chang Hsu, Avik Ray, Hongxia Jin:
Enhancing the generalization for Intent Classification and Out-of-Domain Detection in SLU. ACL/IJCNLP (1) 2021: 2443-2453 - [c11]James Seale Smith, Yen-Chang Hsu, Jonathan Balloch, Yilin Shen, Hongxia Jin, Zsolt Kira:
Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning. ICCV 2021: 9354-9364 - [c10]James Seale Smith, Jonathan Balloch, Yen-Chang Hsu, Zsolt Kira:
Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer. IJCNN 2021: 1-8 - [c9]Ting Hua, Yilin Shen, Changsheng Zhao, Yen-Chang Hsu, Hongxia Jin:
Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding. NAACL-HLT 2021: 2669-2678 - [c8]Junjiao Tian, Dylan Yung, Yen-Chang Hsu, Zsolt Kira:
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition. NeurIPS 2021: 26358-26369 - [i15]James Seale Smith, Jonathan Balloch, Yen-Chang Hsu, Zsolt Kira:
Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer. CoRR abs/2101.09536 (2021) - [i14]James Seale Smith, Yen-Chang Hsu, Jonathan Balloch, Yilin Shen, Hongxia Jin, Zsolt Kira:
Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning. CoRR abs/2106.09701 (2021) - [i13]Yilin Shen, Yen-Chang Hsu, Avik Ray, Hongxia Jin:
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU. CoRR abs/2106.14464 (2021) - [i12]Junjiao Tian, Dylan Yung, Yen-Chang Hsu, Zsolt Kira:
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition. CoRR abs/2110.14577 (2021) - [i11]Junjiao Tian, Yen-Chang Hsu, Yilin Shen, Hongxia Jin, Zsolt Kira:
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data. CoRR abs/2110.15231 (2021) - 2020
- [b1]Yen-Chang Hsu:
Learning from pairwise similarity for visual categorization. Georgia Institute of Technology, Atlanta, GA, USA, 2020 - [c7]Yen-Chang Hsu, Yilin Shen, Hongxia Jin, Zsolt Kira:
Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data. CVPR 2020: 10948-10957 - [c6]Junjiao Tian, Yen-Cheng Liu, Nathaniel Glaser, Yen-Chang Hsu, Zsolt Kira:
Posterior Re-calibration for Imbalanced Datasets. NeurIPS 2020 - [i10]Yen-Chang Hsu, Yilin Shen, Hongxia Jin, Zsolt Kira:
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data. CoRR abs/2002.11297 (2020) - [i9]Junjiao Tian, Yen-Cheng Liu, Nathan Glaser, Yen-Chang Hsu, Zsolt Kira:
Posterior Re-calibration for Imbalanced Datasets. CoRR abs/2010.11820 (2020)
2010 – 2019
- 2019
- [c5]Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser, Phillip Odom, Zsolt Kira:
Multi-class classification without multi-class labels. ICLR (Poster) 2019 - [i8]Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser, Phillip Odom, Zsolt Kira:
Multi-class Classification without Multi-class Labels. CoRR abs/1901.00544 (2019) - 2018
- [c4]Zheng Xu, Yen-Chang Hsu, Jiawei Huang:
Training Student Networks for Acceleration with Conditional Adversarial Networks. BMVC 2018: 61 - [c3]Zheng Xu, Yen-Chang Hsu, Jiawei Huang:
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks. ICLR (Workshop) 2018 - [c2]Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira:
Learning to cluster in order to transfer across domains and tasks. ICLR (Poster) 2018 - [c1]Yen-Chang Hsu, Zheng Xu, Zsolt Kira, Jiawei Huang:
Learning to Cluster for Proposal-Free Instance Segmentation. IJCNN 2018: 1-8 - [i7]Yen-Chang Hsu, Zheng Xu, Zsolt Kira, Jiawei Huang:
Learning to Cluster for Proposal-Free Instance Segmentation. CoRR abs/1803.06459 (2018) - [i6]Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser, Phillip Odom, Zsolt Kira:
A probabilistic constrained clustering for transfer learning and image category discovery. CoRR abs/1806.11078 (2018) - [i5]Yen-Chang Hsu, Yen-Cheng Liu, Zsolt Kira:
Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines. CoRR abs/1810.12488 (2018) - 2017
- [i4]Zheng Xu, Yen-Chang Hsu, Jiawei Huang:
Learning Loss for Knowledge Distillation with Conditional Adversarial Networks. CoRR abs/1709.00513 (2017) - [i3]Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira:
Learning to cluster in order to Transfer across domains and tasks. CoRR abs/1711.10125 (2017) - 2016
- [i2]Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira:
Deep Image Category Discovery using a Transferred Similarity Function. CoRR abs/1612.01253 (2016) - 2015
- [i1]Yen-Chang Hsu, Zsolt Kira:
Neural network-based clustering using pairwise constraints. CoRR abs/1511.06321 (2015)
Coauthor Index
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last updated on 2024-10-11 18:23 CEST by the dblp team
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