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2020 – today
- 2024
[j4]Alec Koppel, Joe Eappen, Sujay Bhatt, Cole Hawkins, Sumitra Ganesh:
Online MCMC Thinning with Kernelized Stein Discrepancy. SIAM J. Math. Data Sci. 6(1): 51-75 (2024)- 2023
- [c5]Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao:
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. EMNLP (Findings) 2023: 2775-2786 - [c4]Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang, Nikolaos Pappas, Vikas Singh, Shuai Zheng:
VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens. NeurIPS 2023 - [i10]Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang, Nikolaos Pappas, Vikas Singh, Shuai Zheng:
Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens. CoRR abs/2305.04241 (2023) - [i9]Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao:
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. CoRR abs/2310.12442 (2023) - 2022
- [b1]Cole Hawkins:
Compressed Training for Uncertainty-Aware Compact Neural Networks. University of California, Santa Barbara, USA, 2022 - [j3]Cole Hawkins, Xing Liu, Zheng Zhang
:
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination. SIAM J. Math. Data Sci. 4(1): 46-71 (2022) - [i8]Cole Hawkins, Alec Koppel, Zheng Zhang:
Online, Informative MCMC Thinning with Kernelized Stein Discrepancy. CoRR abs/2201.07130 (2022) - 2021
- [j2]Kaiqi Zhang, Cole Hawkins, Zheng Zhang:
General-Purpose Bayesian Tensor Learning With Automatic Rank Determination and Uncertainty Quantification. Frontiers Artif. Intell. 4: 668353 (2021) - [j1]Cole Hawkins, Zheng Zhang:
Bayesian tensorized neural networks with automatic rank selection. Neurocomputing 453: 172-180 (2021) - [c3]Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao:
3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low Bitwidth Quantization, and Ultra-Low Latency Acceleration. ACM Great Lakes Symposium on VLSI 2021: 157-162 - [i7]Kaiqi Zhang, Cole Hawkins, Xiyuan Zhang, Cong Hao, Zheng Zhang:
On-FPGA Training with Ultra Memory Reduction: A Low-Precision Tensor Method. CoRR abs/2104.03420 (2021) - [i6]Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao:
3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration. CoRR abs/2105.06250 (2021) - [i5]Cole Hawkins, Vassilis N. Ioannidis, Soji Adeshina, George Karypis:
Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation. CoRR abs/2110.06290 (2021) - [i4]Cole Hawkins, Haichuan Yang, Meng Li, Liangzhen Lai, Vikas Chandra:
Low-Rank+Sparse Tensor Compression for Neural Networks. CoRR abs/2111.01697 (2021) - 2020
- [i3]Cole Hawkins, Zheng Zhang:
End-to-End Variational Bayesian Training of Tensorized Neural Networks with Automatic Rank Determination. CoRR abs/2010.08689 (2020)
2010 – 2019
- 2019
- [c2]Chunfeng Cui, Cole Hawkins, Zheng Zhang:
Tensor Methods for Generating Compact Uncertainty Quantification and Deep Learning Models. ICCAD 2019: 1-6 - [i2]Cole Hawkins, Zheng Zhang:
Bayesian Tensorized Neural Networks with Automatic Rank Selection. CoRR abs/1905.10478 (2019) - 2018
- [c1]Zheng Zhang, Cole Hawkins:
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion. ICDM 2018: 1446-1451 - [i1]Cole Hawkins, Zheng Zhang:
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion. CoRR abs/1809.02153 (2018)
Coauthor Index
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