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IEEE Transactions on Neural Networks and Learning Systems
|
October 8, 2014
Adaptive Batch Mode Active Learning
Shayok Chakraborty, Vineeth Balasubramanian, Sethuraman Panchanathan
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
September 10, 2015
Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds
Shayok Chakraborty, Vineeth Balasubramanian, Qian Sun, et al.
Plos One
|
October 2, 2024
Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy
Yuanying Pang, Ankita Singh, Shayok Chakraborty, et al.
JMIR Aging
|
March 18, 2026
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults Using Source-Free Domain Adaptation: Algorithm Development and Validation
Ronast Subedi, Shayok Chakraborty, Zhe He, et al.
JMIR Aging
|
September 16, 2024
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning
Ankita Singh, Shayok Chakraborty, Zhe He, et al.
Contemporary Clinical Trials
|
August 24, 2025
Introducing the Adherence Promotion with Person-centered Technology (APPT) trial: Rationale, methods, and baseline characteristics
Shenghao Zhang, Michael Dieciuc, Andrew Dilanchian, et al.
Information Processing & Management
|
August 1, 2022
A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training
Zhe He, Shubo Tian, Ankita Singh, et al.
Frontiers in Psychology
|
December 5, 2022
Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacy
Ankita Singh, Shayok Chakraborty, Zhe He, et al.
BMC Digital Health
|
March 17, 2025
New Opportunities for the Early Detection and Treatment of Cognitive Decline: Adherence Challenges and the Promise of Smart and Person-Centered Technologies
Zhe He, Michael Dieciuc, Dawn Carr, et al.
The Gerontologist
|
March 10, 2022
Motivation to Engage in Aging Research: Are There Typologies and Predictors?
Dawn C Carr, Shubo Tian, Zhe He, et al.
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Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
IEEE Transactions on Neural Networks and Learning Systems
|
October 8, 2014
Adaptive Batch Mode Active Learning
Shayok Chakraborty, Vineeth Balasubramanian, Sethuraman Panchanathan
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
September 10, 2015
Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds
Shayok Chakraborty, Vineeth Balasubramanian, Qian Sun, et al.
Plos One
|
October 2, 2024
Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy
Yuanying Pang, Ankita Singh, Shayok Chakraborty, et al.
JMIR Aging
|
March 18, 2026
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults Using Source-Free Domain Adaptation: Algorithm Development and Validation
Ronast Subedi, Shayok Chakraborty, Zhe He, et al.
JMIR Aging
|
September 16, 2024
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning
Ankita Singh, Shayok Chakraborty, Zhe He, et al.
Contemporary Clinical Trials
|
August 24, 2025
Introducing the Adherence Promotion with Person-centered Technology (APPT) trial: Rationale, methods, and baseline characteristics
Shenghao Zhang, Michael Dieciuc, Andrew Dilanchian, et al.
Information Processing & Management
|
August 1, 2022
A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training
Zhe He, Shubo Tian, Ankita Singh, et al.
Frontiers in Psychology
|
December 5, 2022
Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacy
Ankita Singh, Shayok Chakraborty, Zhe He, et al.
BMC Digital Health
|
March 17, 2025
New Opportunities for the Early Detection and Treatment of Cognitive Decline: Adherence Challenges and the Promise of Smart and Person-Centered Technologies
Zhe He, Michael Dieciuc, Dawn Carr, et al.
The Gerontologist
|
March 10, 2022
Motivation to Engage in Aging Research: Are There Typologies and Predictors?
Dawn C Carr, Shubo Tian, Zhe He, et al.
Page
of 1