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1. Blink: A Fully Automated Unsupervised Algorithm for Eye-Blink Detection in EEG Signals

   https://doi.org/10.1109/ALLERTON.2019.8919795  

   Agarwal, Mohit; Sivakumar, Raghupathy (September 2019, Blink: A Fully Automated Unsupervised Algorithm for Eye-Blink Detection in EEG Signals)
2. Science in a Blink: Supporting Ensemble Perception in Scalar Fields

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   Mateevitsi, Victor A; Papka, Michael E; Reda, Khairi (October 2024, IEEE)
3. In the Blink of an Eye: Event-based Emotion Recognition

   https://doi.org/10.1145/3588432.3591511  

   Zhang, Haiwei; Zhang, Jiqing; Dong, Bo; Peers, Pieter; Wu, Wenwei; Wei, Xiaopeng; Heide, Felix; Yang, Xin (July 2023, ACM)
4. Blink: Fast and Generic Collectives for Distributed ML

   Wang, G; Venkataraman, S; Phanishayee, A; Thelin, J; Devanur, N; Stoica, I (March 2020, Conference on Machine Learning and Systems (MLSys))

   Model parameter synchronization across GPUs introduces high overheads for data-parallel training at scale. Existing parameter synchronization protocols cannot effectively leverage available network resources in the face of ever increasing hardware heterogeneity. To address this issue, we propose Blink, a collective communication library that dynamically generates optimal communication primitives by packing spanning trees. We propose techniques to minimize the number of trees generated and extend Blink to leverage heterogeneous communication channels for hybrid, and faster, data transfers. Evaluations show that compared to the state-of-the-art (NCCL), Blink can achieve up to 8× faster model synchronization (AllReduce), and reduce end-to-end DNN training time for image classification tasks by up to 40%. 

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5. Blink to Get In: Biometric Authentication for Mobile Devices using EEG Signals

   https://doi.org/10.1109/ICC40277.2020.9148741  

   Gupta, Ekansh; Agarwal, Mohit; Sivakumar, Raghupathy (June 2020, Blink to Get In: Biometric Authentication for Mobile Devices using EEG Signals)