The open-closed mod-minimizer algorithm.
Algorithms Mol. Biol., December, 2025
Cascade: Enhancing Reinforcement Learning with Curriculum Federated Learning and Interference Avoidance - A Case Study in Adaptive Bitrate Selection.
Proceedings of the IEEE INFOCOM 2024, 2024
Block Aligner: an adaptive SIMD-accelerated aligner for sequences and position-specific scoring matrices.
Bioinform., August, 2023
Knowledge distillation for fast and accurate DNA sequence correction.
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CoRR, 2022
Comment on Dr. Chung's Editorial: Pediatric Health Information Technology - What We Need for Optimal Care of Children.
Appl. Clin. Inform., 2022
Mint: An Accelerator For Mining Temporal Motifs.
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Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022
Evaluating a Vendor-derived Pediatric Sepsis Predictive Model in Acute Care Settings.
Proceedings of the AMIA 2022, 2022
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning.
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CoRR, 2020
Adversarial Shape Perturbations on 3D Point Clouds.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020
AggChecker: A Fact-Checking System for Text Summaries of Relational Data Sets.
Proc. VLDB Endow., 2019
Approximate string searching with fast fourier transforms and simplexes.
PeerJ Prepr., 2019
Adversarial point perturbations on 3D objects.
CoRR, 2019
Verifying Text Summaries of Relational Data Sets.
Proceedings of the 2019 International Conference on Management of Data, 2019
System Demonstration of MRAM Co-designed Processing-in-Memory CNN Accelerator for Mobile and IoT Applications.
Proceedings of the 8th International Workshop on Big Data, 2019
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019
The FactChecker: Verifying Text Summaries of Relational Data Sets.
CoRR, 2018
A computer-based recursion algorithm for automatic charge of power device of electric vehicles carrying electromagnet.
CoRR, 2017
From 0.5 Million to 2.5 Million: Efficiently Scaling up Real-Time Bidding.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015