no code implementations • 14 Mar 2024 • Dimitris Spathis, Aaqib Saeed, Ali Etemad, Sana Tonekaboni, Stefanos Laskaridis, Shohreh Deldari, Chi Ian Tang, Patrick Schwab, Shyam Tailor
This non-archival index is not complete, as some accepted papers chose to opt-out of inclusion.
no code implementations • 4 Jan 2024 • Chi Ian Tang, Lorena Qendro, Dimitris Spathis, Fahim Kawsar, Akhil Mathur, Cecilia Mascolo
These schemes re-purpose contrastive learning for knowledge retention and, Kaizen combines that with self-training in a unified scheme that can leverage unlabelled and labelled data for continual learning.
1 code implementation • 30 Mar 2023 • Chi Ian Tang, Lorena Qendro, Dimitris Spathis, Fahim Kawsar, Cecilia Mascolo, Akhil Mathur
Kaizen is able to balance the trade-off between knowledge retention and learning from new data with an end-to-end model, paving the way for practical deployment of continual learning systems.
1 code implementation • 23 May 2022 • Ekdeep Singh Lubana, Chi Ian Tang, Fahim Kawsar, Robert P. Dick, Akhil Mathur
Federated learning is generally used in tasks where labels are readily available (e. g., next word prediction).
no code implementations • 26 Apr 2022 • Dong Ma, Chi Ian Tang, Cecilia Mascolo
Many deep learning applications, like keyword spotting, require the incorporation of new concepts (classes) over time, referred to as Class Incremental Learning (CIL).
no code implementations • 1 Feb 2022 • Yash Jain, Chi Ian Tang, Chulhong Min, Fahim Kawsar, Akhil Mathur
In this paper, we extend this line of research and present a novel technique called Collaborative Self-Supervised Learning (ColloSSL) which leverages unlabeled data collected from multiple devices worn by a user to learn high-quality features of the data.
no code implementations • 13 Nov 2021 • Kevalee Shah, Dimitris Spathis, Chi Ian Tang, Cecilia Mascolo
Vast quantities of person-generated health data (wearables) are collected but the process of annotating to feed to machine learning models is impractical.
1 code implementation • 11 Feb 2021 • Chi Ian Tang, Ignacio Perez-Pozuelo, Dimitris Spathis, Soren Brage, Nick Wareham, Cecilia Mascolo
Machine learning and deep learning have shown great promise in mobile sensing applications, including Human Activity Recognition.
1 code implementation • 23 Nov 2020 • Chi Ian Tang, Ignacio Perez-Pozuelo, Dimitris Spathis, Cecilia Mascolo
Human Activity Recognition (HAR) constitutes one of the most important tasks for wearable and mobile sensing given its implications in human well-being and health monitoring.