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07/10/2022
Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognition
Increasingly, human behavior is captured on mobile devices, leading to a...
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11/13/2021
HydraGAN A Multi-head, Multi-objective Approach to Synthetic Data Generation
Synthetic data generation overcomes limitations of real-world machine le...
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11/08/2021
Mimic: An adaptive algorithm for multivariate time series classification
Time series data are valuable but are often inscrutable. Gaining trust i...
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09/30/2021
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning
Unsupervised domain adaptation (UDA) provides a strategy for improving m...
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07/12/2020
Transfer Learning for Activity Recognition in Mobile Health
While activity recognition from inertial sensors holds potential for mob...
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05/22/2020
Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data
Domain adaptation (DA) offers a valuable means to reuse data and models ...
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09/10/2019
Techniques All Classifiers Can Learn from Deep Networks: Models, Optimizations, and Regularization
Deep neural networks have introduced novel and useful tools to the machi...
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07/17/2019
Multi-Purposing Domain Adaptation Discriminators for Pseudo Labeling Confidence
Often domain adaptation is performed using a discriminator (domain class...
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07/12/2019
Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence Model
Recognizing activities of daily living (ADLs) plays an essential role in...
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12/06/2018