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2020 – today
- 2024
[j15]Hu Jiang, Qiang Zou, Yunqiang Zhu, Yong Li, Bin Zhou, Wentao Zhou, Shunyu Yao, Xiaoliang Dai
, Hongkun Yao, Siyu Chen:
Deep learning prediction of rainfall-driven debris flows considering the similar critical thresholds within comparable background conditions. Environ. Model. Softw. 179: 106130 (2024)- [j14]Weirong Li, Kai Sun, Yunqiang Zhu, Fangyu Ding, Lei Hu, Xiaoliang Dai, Jia Song, Jie Yang, Lang Qian, Shu Wang:
GeoTPE: A neural network model for geographical topic phrases extraction from literature based on BERT enhanced with relative position embedding. Expert Syst. Appl. 235: 121077 (2024) - [j13]Chaojian Li, Kyungmin Kim, Bichen Wu, Peizhao Zhang, Hang Zhang, Xiaoliang Dai, Peter Vajda, Yingyan (Celine) Lin:
An Investigation on Hardware-Aware Vision Transformer Scaling. ACM Trans. Embed. Comput. Syst. 23(3): 52:1-52:19 (2024) - [j12]Weirong Li, Kai Sun, Shu Wang, Yunqiang Zhu, Xiaoliang Dai, Lei Hu:
DePNR: A DeBERTa-based deep learning model with complete position embedding for place name recognition from geographical literature. Trans. GIS 28(5): 993-1020 (2024) - [c22]Felix Wimbauer, Bichen Wu, Edgar Schönfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam S. Tsai, Jonas Kohler, Christian Rupprecht, Daniel Cremers, Peter Vajda, Jialiang Wang:
Cache Me if You Can: Accelerating Diffusion Models through Block Caching. CVPR 2024: 6211-6220 - [c21]Qilong Zhangli, Jindong Jiang, Di Liu, Licheng Yu, Xiaoliang Dai, Ankit Ramchandani, Guan Pang, Dimitris N. Metaxas, Praveen Krishnan:
Layout-Agnostic Scene Text Image Synthesis with Diffusion Models. CVPR 2024: 7496-7506 - [c20]Yunyang Xiong, Bala Varadarajan, Lemeng Wu, Xiaoyu Xiang, Fanyi Xiao, Chenchen Zhu, Xiaoliang Dai, Dilin Wang, Fei Sun, Forrest N. Iandola, Raghuraman Krishnamoorthi, Vikas Chandra:
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything. CVPR 2024: 16111-16121 - [c19]Bolin Lai, Xiaoliang Dai, Lawrence Chen, Guan Pang, James M. Rehg, Miao Liu:
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning. ECCV (9) 2024: 135-155 - [i34]Qilong Zhangli, Jindong Jiang, Di Liu, Licheng Yu, Xiaoliang Dai, Ankit Ramchandani, Guan Pang, Dimitris N. Metaxas, Praveen Krishnan:
SceneTextGen: Layout-Agnostic Scene Text Image Synthesis with Diffusion Models. CoRR abs/2406.01062 (2024) - [i33]Yuewei Yang, Jialiang Wang, Xiaoliang Dai, Peizhao Zhang, Hongbo Zhang:
An Analysis on Quantizing Diffusion Transformers. CoRR abs/2406.11100 (2024) - 2023
- [j11]Xiaoliang Dai, Yunqiang Zhu, Kai Sun, Qiang Zou, Shen Zhao, Weirong Li, Lei Hu, Shu Wang:
Examining the Spatially Varying Relationships between Landslide Susceptibility and Conditioning Factors Using a Geographical Random Forest Approach: A Case Study in Liangshan, China. Remote. Sens. 15(6): 1513 (2023) - [c18]Feng Liang, Bichen Wu, Xiaoliang Dai, Kunpeng Li, Yinan Zhao, Hang Zhang, Peizhao Zhang, Peter Vajda, Diana Marculescu:
Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP. CVPR 2023: 7061-7070 - [c17]Junjiao Tian, Xiaoliang Dai, Chih-Yao Ma, Zecheng He, Yen-Cheng Liu, Zsolt Kira:
Trainable Projected Gradient Method for Robust Fine-Tuning. CVPR 2023: 7836-7845 - [c16]Ji Hou, Xiaoliang Dai, Zijian He, Angela Dai, Matthias Nießner:
Mask3D: Pretraining 2D Vision Transformers by Learning Masked 3D Priors. CVPR 2023: 13510-13519 - [c15]Haoran You, Yunyang Xiong, Xiaoliang Dai, Bichen Wu, Peizhao Zhang, Haoqi Fan, Peter Vajda, Yingyan Celine Lin:
Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference. CVPR 2023: 14431-14442 - [c14]Yonggan Fu, Yuecheng Li, Chenghui Li, Jason M. Saragih, Peizhao Zhang, Xiaoliang Dai, Yingyan Celine Lin:
Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence. CVPR 2023: 21036-21045 - [c13]Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer, Judy Hoffman:
Token Merging: Your ViT But Faster. ICLR 2023 - [c12]Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen, Wei Wen:
NASRec: Weight Sharing Neural Architecture Search for Recommender Systems. WWW 2023: 1199-1207 - [i32]Sayan Ghosh, Karthik Prasad, Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Graham Cormode, Peter Vajda:
Pruning Compact ConvNets for Efficient Inference. CoRR abs/2301.04502 (2023) - [i31]Ji Hou, Xiaoliang Dai, Zijian He, Angela Dai, Matthias Nießner:
Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors. CoRR abs/2302.14746 (2023) - [i30]Junjiao Tian, Xiaoliang Dai, Chih-Yao Ma, Zecheng He, Yen-Cheng Liu, Zsolt Kira:
Trainable Projected Gradient Method for Robust Fine-tuning. CoRR abs/2303.10720 (2023) - [i29]Yonggan Fu, Yuecheng Li, Chenghui Li, Jason M. Saragih, Peizhao Zhang, Xiaoliang Dai, Yingyan Lin:
Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence. CoRR abs/2304.11835 (2023) - [i28]Zhihang Yu, Shu Wang, Yunqiang Zhu, Wen Yuan, Xiaoliang Dai, Zhiqiang Zou:
Unveiling Optimal SDG Pathways: An Innovative Approach Leveraging Graph Pruning and Intent Graph for Effective Recommendations. CoRR abs/2309.11741 (2023) - [i27]Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam S. Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, Matthew Yu, Abhishek Kadian, Filip Radenovic, Dhruv Mahajan, Kunpeng Li, Yue Zhao, Vladan Petrovic, Mitesh Kumar Singh, Simran Motwani, Yi Wen, Yiwen Song, Roshan Sumbaly, Vignesh Ramanathan, Zijian He, Peter Vajda, Devi Parikh:
Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack. CoRR abs/2309.15807 (2023) - [i26]Yunyang Xiong, Bala Varadarajan, Lemeng Wu, Xiaoyu Xiang, Fanyi Xiao, Chenchen Zhu, Xiaoliang Dai, Dilin Wang, Fei Sun, Forrest N. Iandola, Raghuraman Krishnamoorthi, Vikas Chandra:
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything. CoRR abs/2312.00863 (2023) - [i25]Felix Wimbauer, Bichen Wu, Edgar Schönfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam S. Tsai, Jonas Kohler, Christian Rupprecht, Daniel Cremers, Peter Vajda, Jialiang Wang:
Cache Me if You Can: Accelerating Diffusion Models through Block Caching. CoRR abs/2312.03209 (2023) - [i24]Bolin Lai, Xiaoliang Dai, Lawrence Chen, Guan Pang, James M. Rehg, Miao Liu:
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning. CoRR abs/2312.03849 (2023) - [i23]Yuewei Yang, Xiaoliang Dai, Jialiang Wang, Peizhao Zhang, Hongbo Zhang:
Efficient Quantization Strategies for Latent Diffusion Models. CoRR abs/2312.05431 (2023) - 2022
- [j10]Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha:
CURIOUS: Efficient Neural Architecture Search Based on a Performance Predictor and Evolutionary Search. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(11): 4975-4990 (2022) - [j9]Xiaoliang Dai, Hongxu Yin, Niraj K. Jha:
Incremental Learning Using a Grow-and-Prune Paradigm With Efficient Neural Networks. IEEE Trans. Emerg. Top. Comput. 10(2): 752-762 (2022) - [j8]Wenhan Xia, Hongxu Yin, Xiaoliang Dai, Niraj K. Jha:
Fully Dynamic Inference With Deep Neural Networks. IEEE Trans. Emerg. Top. Comput. 10(2): 962-972 (2022) - [c11]Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma, Yen-Cheng Liu, Kan Chen, Bichen Wu, Zijian He, Kris Kitani, Peter Vajda:
Cross-Domain Adaptive Teacher for Object Detection. CVPR 2022: 7571-7580 - [c10]Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Judy Hoffman:
Hydra Attention: Efficient Attention with Many Heads. ECCV Workshops (7) 2022: 35-49 - [c9]Yen-Cheng Liu, Chih-Yao Ma, Xiaoliang Dai, Junjiao Tian, Peter Vajda, Zijian He, Zsolt Kira:
Open-Set Semi-Supervised Object Detection. ECCV (30) 2022: 143-159 - [i22]Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen, Wei Wen:
NASRec: Weight Sharing Neural Architecture Search for Recommender Systems. CoRR abs/2207.07187 (2022) - [i21]Yen-Cheng Liu, Chih-Yao Ma, Xiaoliang Dai, Junjiao Tian, Peter Vajda, Zijian He, Zsolt Kira:
Open-Set Semi-Supervised Object Detection. CoRR abs/2208.13722 (2022) - [i20]Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Judy Hoffman:
Hydra Attention: Efficient Attention with Many Heads. CoRR abs/2209.07484 (2022) - [i19]Feng Liang, Bichen Wu, Xiaoliang Dai, Kunpeng Li, Yinan Zhao, Hang Zhang, Peizhao Zhang, Peter Vajda, Diana Marculescu:
Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP. CoRR abs/2210.04150 (2022) - [i18]Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer, Judy Hoffman:
Token Merging: Your ViT But Faster. CoRR abs/2210.09461 (2022) - [i17]Yu-Jhe Li, Tao Xu, Bichen Wu, Ningyuan Zheng, Xiaoliang Dai, Albert Pumarola, Peizhao Zhang, Peter Vajda, Kris Kitani:
3D-Aware Encoding for Style-based Neural Radiance Fields. CoRR abs/2211.06583 (2022) - [i16]Haoran You, Yunyang Xiong, Xiaoliang Dai, Bichen Wu, Peizhao Zhang, Haoqi Fan, Peter Vajda, Yingyan Lin:
Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference. CoRR abs/2211.10526 (2022) - 2021
- [j7]Hongxu Yin, Bilal Mukadam, Xiaoliang Dai, Niraj K. Jha:
DiabDeep: Pervasive Diabetes Diagnosis Based on Wearable Medical Sensors and Efficient Neural Networks. IEEE Trans. Emerg. Top. Comput. 9(3): 1139-1150 (2021) - [j6]Ayten Ozge Akmandor, Xiaoliang Dai, Niraj K. Jha:
YSUY: Your Smartphone Understands You - Using Machine Learning to Address Fundamental Human Needs. IEEE Trans. Syst. Man Cybern. Syst. 51(12): 7553-7568 (2021) - [c8]Kyungmin Kim, Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Zhicheng Yan, Peter Vajda, Seon Joo Kim:
Rethinking the Self-Attention in Vision Transformers. CVPR Workshops 2021: 3071-3075 - [c7]Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli:
FP-NAS: Fast Probabilistic Neural Architecture Search. CVPR 2021: 15139-15148 - [c6]Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez:
FBNetV3: Joint Architecture-Recipe Search Using Predictor Pretraining. CVPR 2021: 16276-16285 - [c5]Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Zhicheng Yan, Masayoshi Tomizuka, Joseph Gonzalez, Kurt Keutzer, Peter Vajda:
Visual Transformers: Where Do Transformers Really Belong in Vision Models? ICCV 2021: 579-589 - [i15]Bichen Wu, Chaojian Li, Hang Zhang, Xiaoliang Dai, Peizhao Zhang, Matthew Yu, Jialiang Wang, Yingyan Lin, Peter Vajda:
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run. CoRR abs/2111.10007 (2021) - [i14]Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma, Yen-Cheng Liu, Kan Chen, Bichen Wu, Zijian He, Kris Kitani, Peter Vajda:
Cross-Domain Object Detection via Adaptive Self-Training. CoRR abs/2111.13216 (2021) - 2020
- [j5]Xiaoliang Dai, Hongxu Yin, Niraj K. Jha:
Grow and Prune Compact, Fast, and Accurate LSTMs. IEEE Trans. Computers 69(3): 441-452 (2020) - [c4]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CVPR 2020: 12962-12971 - [i13]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CoRR abs/2004.05565 (2020) - [i12]Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez:
FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function. CoRR abs/2006.02049 (2020) - [i11]Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Masayoshi Tomizuka, Kurt Keutzer, Peter Vajda:
Visual Transformers: Token-based Image Representation and Processing for Computer Vision. CoRR abs/2006.03677 (2020) - [i10]Wenhan Xia, Hongxu Yin, Xiaoliang Dai, Niraj K. Jha:
Fully Dynamic Inference with Deep Neural Networks. CoRR abs/2007.15151 (2020) - [i9]Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli:
FP-NAS: Fast Probabilistic Neural Architecture Search. CoRR abs/2011.10949 (2020)
2010 – 2019
- 2019
- [b1]Xiaoliang Dai:
Synthesis of Efficient Neural Networks. Princeton University, USA, 2019 - [j4]Xiaoliang Dai, Hongxu Yin, Niraj K. Jha:
NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm. IEEE Trans. Computers 68(10): 1487-1497 (2019) - [c3]Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer:
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search. CVPR 2019: 10734-10742 - [c2]Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K. Jha:
ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation. CVPR 2019: 11398-11407 - [i8]Xiaoliang Dai, Hongxu Yin, Niraj K. Jha:
Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks. CoRR abs/1905.10952 (2019) - [i7]Hongxu Yin, Bilal Mukadam, Xiaoliang Dai, Niraj K. Jha:
DiabDeep: Pervasive Diabetes Diagnosis based on Wearable Medical Sensors and Efficient Neural Networks. CoRR abs/1910.04925 (2019) - [i6]Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha:
STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods. CoRR abs/1912.05831 (2019) - 2018
- [j3]Arsalan Mosenia, Xiaoliang Dai, Prateek Mittal, Niraj K. Jha:
PinMe: Tracking a Smartphone User around the World. IEEE Trans. Multi Scale Comput. Syst. 4(3): 420-435 (2018) - [i5]Arsalan Mosenia, Xiaoliang Dai, Prateek Mittal, Niraj K. Jha:
PinMe: Tracking a Smartphone User around the World. CoRR abs/1802.01468 (2018) - [i4]Xiaoliang Dai, Hongxu Yin, Niraj K. Jha:
Grow and Prune Compact, Fast, and Accurate LSTMs. CoRR abs/1805.11797 (2018) - [i3]Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer:
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search. CoRR abs/1812.03443 (2018) - [i2]Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K. Jha:
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation. CoRR abs/1812.08934 (2018) - 2017
- [j2]Xiaoliang Dai, Niraj K. Jha:
Improving Convergence and Simulation Time of Quantum Hydrodynamic Simulation: Application to Extraction of Best 10-nm FinFET Parameter Values. IEEE Trans. Very Large Scale Integr. Syst. 25(1): 319-329 (2017) - [j1]Xiaoliang Dai, Niraj K. Jha:
Using a Device State Library to Boost the Performance of TCAD Mixed-Mode Simulation. IEEE Trans. Very Large Scale Integr. Syst. 25(9): 2616-2624 (2017) - [i1]Xiaoliang Dai, Hongxu Yin, Niraj K. Jha:
NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm. CoRR abs/1711.02017 (2017)
2000 – 2009
- 2008
- [c1]Feng Yang, Xiaoliang Dai, Ruzhi Xu:
The Common Problems on the Peer-to-Peer Multicast Overlay Networks. CSSE (3) 2008: 98-101
Coauthor Index
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