Works (4)

2018 article

Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach

Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach. PROCEEDINGS OF THE 26TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (UMAP'18), pp. 43–51.

By: S. Shen, M. Ausin, B. Mostafavi & M. Chi

Source: Web Of Science
Added: April 2, 2019

2016 conference paper

An analysis of feature selection and reward function for model-based reinforcement learning

Intelligent tutoring systems, its 2016, 0684, 504–505.

By: S. Shen, C. Lin, B. Mostafavi, T. Barnes & M. Chi

Source: NC State University Libraries
Added: August 6, 2018

2015 review

Anomaly detection in dynamic networks: A survey

[Review of ]. Wiley Interdisciplinary Reviews: Computational Statistics, 7(3), 223–247.

By: S. Ranshous, S. Shen, D. Koutra, S. Harenberg, C. Faloutsos & N. Samatova

Source: NC State University Libraries
Added: August 6, 2018

report

Anomaly detection in dynamic networks: A survey

Ranshous, S., Shen, S., Koutra, D., Faloutsos, C., & Samatova, N. F. In Technical Report- Not held in TRLN member libraries.

By: S. Ranshous, S. Shen, D. Koutra, C. Faloutsos & N. Samatova

Source: NC State University Libraries
Added: August 6, 2018