Cole Hawkins

According to our database1, Cole Hawkins authored at least 16 papers between 2018 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
Online MCMC Thinning with Kernelized Stein Discrepancy.
SIAM J. Math. Data Sci., March, 2024

2023
VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Compressed Training for Uncertainty-Aware Compact Neural Networks.
PhD thesis, 2022

Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination.
SIAM J. Math. Data Sci., 2022

Online, Informative MCMC Thinning with Kernelized Stein Discrepancy.
CoRR, 2022

2021
Bayesian tensorized neural networks with automatic rank selection.
Neurocomputing, 2021

General-Purpose Bayesian Tensor Learning With Automatic Rank Determination and Uncertainty Quantification.
Frontiers Artif. Intell., 2021

Low-Rank+Sparse Tensor Compression for Neural Networks.
CoRR, 2021

Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation.
CoRR, 2021

3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration.
CoRR, 2021

On-FPGA Training with Ultra Memory Reduction: A Low-Precision Tensor Method.
CoRR, 2021

3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low Bitwidth Quantization, and Ultra-Low Latency Acceleration.
Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

2020
End-to-End Variational Bayesian Training of Tensorized Neural Networks with Automatic Rank Determination.
CoRR, 2020

2019
Tensor Methods for Generating Compact Uncertainty Quantification and Deep Learning Models.
Proceedings of the International Conference on Computer-Aided Design, 2019

2018
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion.
Proceedings of the IEEE International Conference on Data Mining, 2018


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