Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Denis Larocque"'
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 5, Pp 238-250 (2024)
We introduce MuJAM, an adaptive traffic signal control method which leverages model-based reinforcement learning to 1) extend recent generalization efforts (to road network architectures and traffic distributions) further by allowing a generalization
Externí odkaz:
https://doaj.org/article/92d2952a76ca4d67b5b5d94108b55636
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 5, Pp 2-15 (2024)
A number of deep reinforcement-learning (RL) approaches propose to control traffic signals. Compared to traditional approaches, RL approaches can learn from higher-dimensionality input road and vehicle sensors and better adapt to varying traffic cond
Externí odkaz:
https://doaj.org/article/9c2c683dbf4a4cc98f2824e41e3b8b20
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-19 (2023)
Abstract Capturing the conditional covariances or correlations among the elements of a multivariate response vector based on covariates is important to various fields including neuroscience, epidemiology and biomedicine. We propose a new method calle
Externí odkaz:
https://doaj.org/article/845617a899a24aca92176de3d4cb04df
Publikováno v:
Entropy, Vol 22, Iss 12, p 1363 (2020)
We present an unsupervised method to detect anomalous time series among a collection of time series. To do so, we extend traditional Kernel Density Estimation for estimating probability distributions in Euclidean space to Hilbert spaces. The estimate
Externí odkaz:
https://doaj.org/article/0f721c59e41c42c7b7e1531eac0921af
Akademický článek
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Autor:
Denis-Larocque, Gabrielle, Williams, Karl, St-Sauveur, Isabelle, Ruddy, Margaret, Rennick, Janet
Publikováno v:
In Intensive & Critical Care Nursing December 2017 43:149-155
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:7496-7507
Scaling adaptive traffic-signal control involves dealing with combinatorial state and action spaces. Multi-agent reinforcement learning attempts to address this challenge by distributing control to specialized agents. However, specialization hinders
Autor:
Tsimicalis, Argerie, Denis-Larocque, Gabrielle, Michalovic, Alisha, Lepage, Carolann, Williams, Karl, Yao, Tian-Ran, Palomo, Telma, Dahan-Oliel, Noemi, Le May, Sylvie, Rauch, Frank
Publikováno v:
Quality of Life Research, 2016 Aug 01. 25(8), 1877-1896.
Externí odkaz:
https://www.jstor.org/stable/44852480
Publikováno v:
Journal of Marketing Analytics. 9:173-184
Advertisements are a central source of revenue for free-to-play games. However, they could decrease in-app purchases (IAP) by reducing the quality of user experience or by causing early churn. We analyzed more than 50 million advertisements viewed in