Luke Buquicchio

Orcid: 0000-0002-9639-8660

According to our database1, Luke Buquicchio authored at least 26 papers between 2019 and 2023.

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Bibliography

2023
INPHOVIS: Interactive visual analytics for smartphone-based digital phenotyping.
Vis. Informatics, June, 2023

Domain Adaptation Methods for Lab-to-Field Human Context Recognition.
Sensors, March, 2023

Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Population-Level Visual Analytics of Smartphone Sensed Health and Wellness Using Community Phenotypes.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

Adversarial Human Context Recognition: Evasion Attacks and Defenses.
Proceedings of the 47th IEEE Annual Computers, Software, and Applications Conference, 2023

Stabilizing Adversarial Training for Generative Networks.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Positive Unlabeled Learning with a Sequential Selection Bias.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Triplet-based Domain Adaptation (Triple-DARE) for Lab-to-field Human Context Recognition.
Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2022

Robust Recurrent Classifier Chains for Multi-Label Learning with Missing Labels.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Recovering the Propensity Score from Biased Positive Unlabeled Data.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
ARGUS: Interactive visual analysis of disruptions in smartphone-detected Bio-Behavioral Rhythms.
Vis. Informatics, 2021

Smartphone Health Biomarkers: Positive Unlabeled Learning of In-the-Wild Contexts.
IEEE Pervasive Comput., 2021

Visual Analytics of Smartphone-Sensed Human Behavior and Health.
IEEE Computer Graphics and Applications, 2021

CARTMAN: Complex Activity Recognition Using Topic Models for Feature Generation from Wearable Sensor Data.
Proceedings of the IEEE International Conference on Smart Computing, 2021

Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PLEADES: Population Level Observation of Smartphone Sensed Symptoms for In-the-wild Data using Clustering.
Proceedings of the 16th International Joint Conference on Computer Vision, 2021

Local Geometry Preserving Deep Networks For Featurizing High Dimensional Datasets.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Few-Shot Classification for Human Context Recognition Using Smartphone Data Traces.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Exploratory Data Analysis of Population Level Smartphone-Sensed Data.
Proceedings of the Computer Vision, Imaging and Computer Graphics Theory and Applications, 2021

GAN for Generating User-Specific Human Activity Data From An Incomplete Training Corpus.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Variational Open Set Recognition (VOSR).
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
ARGUS: Interactive Visual Analytics Framework for the Discovery of Disruptions in Bio-Behavioral Rhythms.
Proceedings of the 22nd Eurographics Conference on Visualization, 2020

DeepContext: Parameterized Compatibility-Based Attention CNN for Human Context Recognition.
Proceedings of the IEEE 14th International Conference on Semantic Computing, 2020

INTOSIS: Interactive Observation of Smartphone Inferred Symptoms for In-The-Wild Data.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

BurstPU: Classification of Weakly Labeled Datasets with Sequential Bias.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
COMEX: Identifying Mislabeled Human Behavioral Context Data Using Visual Analytics.
Proceedings of the 43rd IEEE Annual Computer Software and Applications Conference, 2019


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