Shitian Shen

Works (4)

Updated: July 5th, 2023 15:39

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 n, M. Ausin  n, B. Mostafavi n & M. Chi n

author keywords: Constrained Reinforcement Learning; POMDP; Intelligent Tutoring System
TL;DR: This work constructs a general data-driven framework called Constrained Action-based Partially Observable Markov Decision Process (CAPOMDP) to induce effective pedagogical policies and induces two types of policies: CAPOMDPLG using learning gain as reward with the goal of improving students' learning performance, and CAPomDPTime using time as reward for reducing students' time on task. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
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 n, S. Shen n, D. Koutra *, S. Harenberg n, C. Faloutsos* & N. Samatova n

author keywords: anomaly detection; dynamic networks; outlier detection; graph mining; dynamic network anomaly detection; network anomaly detection
TL;DR: This work focuses on anomaly detection in static graphs, which do not change and are capable of representing only a single snapshot of data, but as real‐world networks are constantly changing, there has been a shift in focus to dynamic graphs,Which evolve over time. (via Semantic Scholar)
Source: Web Of Science
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

Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.

Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.