Cole Hawkins

22 papers A* 2A 1Journal 15Unranked 3
YearRankTypeTitle / Venue / Authors
2025 — conf
Sequence-level Large Language Model Training with Contrastive Preference Optimization.
NAACL (Findings)
Zhili Feng, Dhananjay Ram, Cole Hawkins, Aditya Rawal, Jinman Zhao, Sheng Zha
2025 J jnl
Sequence-level Large Language Model Training with Contrastive Preference Optimization.
CoRR
Zhili Feng, Dhananjay Ram, Cole Hawkins, Aditya Rawal, Jinman Zhao, Sheng Zha
2024 J jnl
Online MCMC Thinning with Kernelized Stein Discrepancy.
SIAM J. Math. Data Sci.
Alec Koppel, Joe Eappen, Sujay Bhatt, Cole Hawkins, Sumitra Ganesh
2023 — conf
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer.
EMNLP (Findings)
Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
2023 J jnl
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer.
CoRR
Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
2023 A* conf
VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens.
NeurIPS
Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang, Nikolaos Pappas, Vikas Singh, Shuai Zheng
2023 J jnl
Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens.
CoRR
Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang, Nikolaos Pappas, Vikas Singh, Shuai Zheng
2022 — —
Compressed Training for Uncertainty-Aware Compact Neural Networks.
Cole Hawkins
2022 J jnl
Online, Informative MCMC Thinning with Kernelized Stein Discrepancy.
CoRR
Cole Hawkins, Alec Koppel, Zheng Zhang
2022 J jnl
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination.
SIAM J. Math. Data Sci.
Cole Hawkins, Xing Liu, Zheng Zhang
2021 — conf
3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low Bitwidth Quantization, and Ultra-Low Latency Acceleration.
ACM Great Lakes Symposium on VLSI
Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao
2021 J jnl
3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration.
CoRR
Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao
2021 J jnl
Bayesian tensorized neural networks with automatic rank selection.
Neurocomputing
Cole Hawkins, Zheng Zhang
2021 J jnl
General-Purpose Bayesian Tensor Learning With Automatic Rank Determination and Uncertainty Quantification.
Frontiers Artif. Intell.
Kaiqi Zhang, Cole Hawkins, Zheng Zhang
2021 J jnl
Low-Rank+Sparse Tensor Compression for Neural Networks.
CoRR
Cole Hawkins, Haichuan Yang, Meng Li, Liangzhen Lai, Vikas Chandra
2021 J jnl
On-FPGA Training with Ultra Memory Reduction: A Low-Precision Tensor Method.
CoRR
Kaiqi Zhang, Cole Hawkins, Xiyuan Zhang, Cong Hao, Zheng Zhang
2021 J jnl
Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation.
CoRR
Cole Hawkins, Vassilis N. Ioannidis, Soji Adeshina, George Karypis
2020 J jnl
End-to-End Variational Bayesian Training of Tensorized Neural Networks with Automatic Rank Determination.
CoRR
Cole Hawkins, Zheng Zhang
2019 J jnl
Bayesian Tensorized Neural Networks with Automatic Rank Selection.
CoRR
Cole Hawkins, Zheng Zhang
2019 A conf
Tensor Methods for Generating Compact Uncertainty Quantification and Deep Learning Models.
ICCAD
Chunfeng Cui, Cole Hawkins, Zheng Zhang
2018 A* conf
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion.
ICDM
Zheng Zhang, Cole Hawkins
2018 J jnl
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion.
CoRR
Cole Hawkins, Zheng Zhang