Jesse Hoey mostly deals with Dementia, Partially observable Markov decision process, Human–computer interaction, Artificial intelligence and Markov decision process. His Partially observable Markov decision process research includes elements of Bellman equation, Reinforcement learning and Bayesian inference. The concepts of his Human–computer interaction study are interwoven with issues in Emotion recognition, Activity recognition and Gesture.
His study in Machine learning extends to Artificial intelligence with its themes. His Markov decision process research is multidisciplinary, incorporating elements of Mathematical optimization and Markov chain. His Dynamic programming study in the realm of Mathematical optimization interacts with subjects such as Class, Space and Application domain.
The scientist’s investigation covers issues in Artificial intelligence, Human–computer interaction, Affect control theory, Partially observable Markov decision process and Markov decision process. His specific area of interest is Artificial intelligence, where Jesse Hoey studies Hidden Markov model. His research in Hidden Markov model intersects with topics in Activity recognition, Anomaly detection and Training set.
He connects Human–computer interaction with Dementia in his research. His Partially observable Markov decision process research incorporates elements of Rehabilitation and Bayesian probability. His Markov decision process study combines topics from a wide range of disciplines, such as Mathematical optimization and Markov chain.
Jesse Hoey spends much of his time researching Affect control theory, Artificial intelligence, Affect, Affective computing and Cognitive science. Other disciplines of study, such as Function and Dementia, are mixed together with his Affect control theory studies. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning, Personality psychology and Natural language processing.
His Affective computing study is related to the wider topic of Human–computer interaction. His Human–computer interaction study integrates concerns from other disciplines, such as End user and Medical education. His work in Facial expression addresses issues such as Emotion recognition, which are connected to fields such as Group emotion and Protocol.
His primary areas of study are Affect control theory, Affect, Function, Dementia and Affective computing. The study incorporates disciplines such as Identity and Cognitive psychology, Set in addition to Affect control theory. The Set study combines topics in areas such as Developmental psychology, Persona and Activities of daily living.
His Affect research is multidisciplinary, relying on both Emotion recognition, Speech recognition and Facial expression. His Speech recognition research includes themes of Protocol, Group emotion and Human–computer interaction. Jesse Hoey combines subjects such as Word, Cognitive science, Natural language and Conversation with his study of Affective computing.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Sensor-Based Activity Recognition
Liming Chen;J. Hoey;C. D. Nugent;D. J. Cook.
systems man and cybernetics (2012)
SPUDD: stochastic planning using decision diagrams
Jesse Hoey;Robert St-Aubin;Alan Hu;Craig Boutilier.
uncertainty in artificial intelligence (1999)
The COACH prompting system to assist older adults with dementia through handwashing: An efficacy study
Alex Mihailidis;Alex Mihailidis;Jennifer N Boger;Jennifer N Boger;Tammy Craig;Jesse Hoey.
BMC Geriatrics (2008)
An analytic solution to discrete Bayesian reinforcement learning
Pascal Poupart;Nikos Vlassis;Jesse Hoey;Kevin Regan.
international conference on machine learning (2006)
Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process
Jesse Hoey;Pascal Poupart;Axel von Bertoldi;Tammy Craig.
Computer Vision and Image Understanding (2010)
A decision-theoretic approach to task assistance for persons with dementia
Jennifer Boger;Pascal Poupart;Jesse Hoey;Craig Boutilier.
international joint conference on artificial intelligence (2005)
A planning system based on Markov decision processes to guide people with dementia through activities of daily living
J. Boger;J. Hoey;P. Poupart;C. Boutilier.
international conference of the ieee engineering in medicine and biology society (2006)
Assisting persons with dementia during handwashing using a partially observable Markov decision process.
Jesse Hoey;Axel von Bertoldi;Pascal Poupart;Alex Mihailidis.
international conference on computer vision systems (2007)
Body Movements for Affective Expression: A Survey of Automatic Recognition and Generation
Michelle Karg;Ali-Akbar Samadani;Rob Gorbet;Kolja Kuhnlenz.
IEEE Transactions on Affective Computing (2013)
APRICODD: Approximate Policy Construction Using Decision Diagrams
Robert St-Aubin;Jesse Hoey;Craig Boutilier.
neural information processing systems (2000)
Profile was last updated on December 6th, 2021.
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