Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Jeremy E. Block"'
Autor:
Jeremy E. Block, Ilana Bookner, Sharon Lynn Chu, R. Jordan Crouser, Donald R. Honeycutt, Rebecca M. Jonas, Abhishek Kulkarni, Yancy Vance Paredes, Eric D. Ragan
Publikováno v:
Analytics, Vol 2, Iss 2, Pp 509-529 (2023)
Analyst sensemaking research typically focuses on individual or small groups conducting intelligence tasks. This has helped understand information retrieval tasks and how people communicate information. As a part of the grand challenge of the Summer
Externí odkaz:
https://doaj.org/article/87e6bec6d0f649f497551c0ee463ac57
Autor:
Chiradeep Roy, Mahsan Nourani, Donald R. Honeycutt, Jeremy E. Block, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
Abstract We consider the following activity recognition task: given a video, infer the set of activities being performed in the video and assign each frame to an activity. This task can be solved using modern deep learning architectures based on neur
Externí odkaz:
https://doaj.org/article/56000094290e49ed902d912c15a5afec
Autor:
Mahsan Nourani, Chiradeep Roy, Jeremy E. Block, Donald R. Honeycutt, Tahrima Rahman, Eric D. Ragan, Vibhav Gogate
Publikováno v:
ACM Transactions on Interactive Intelligent Systems. 12:1-29
While EXplainable Artificial Intelligence (XAI) approaches aim to improve human-AI collaborative decision-making by improving model transparency and mental model formations, experiential factors associated with human users can cause challenges in way
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cf05125c347dd36502e5d5971f8b062
https://doi.org/10.1145/3531066
https://doi.org/10.1145/3531066
Autor:
Ragan, Jeremy E. Block, Ilana Bookner, Sharon Lynn Chu, R. Jordan Crouser, Donald R. Honeycutt, Rebecca M. Jonas, Abhishek Kulkarni, Yancy Vance Paredes, Eric D.
Publikováno v:
Analytics; Volume 2; Issue 2; Pages: 509-529
Analyst sensemaking research typically focuses on individual or small groups conducting intelligence tasks. This has helped understand information retrieval tasks and how people communicate information. As a part of the grand challenge of the Summer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::57e013ccee96ff06f5fccfd6256dd481
Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish common ground a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e7a64ec2f441a5f067e6fe32bbb6d9f
Autor:
Tahrima Rahman, Mahsan Nourani, Vibhav Gogate, Donald R. Honeycutt, Jeremy E. Block, Eric D. Ragan, Chiradeep Roy
Publikováno v:
IUI
EXplainable Artificial Intelligence (XAI) approaches are used to bring transparency to machine learning and artificial intelligence models, and hence, improve the decision-making process for their end-users. While these methods aim to improve human u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::806244d17eb17aeefe8a3fc982b54cd9
https://doi.org/10.1145/3397481.3450639
https://doi.org/10.1145/3397481.3450639
Publikováno v:
IUI
Research in interpretable machine learning proposes different computational and human subject approaches to evaluate model saliency explanations. These approaches measure different qualities of explanations to achieve diverse goals in designing inter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46e87e7811d4abe38db18e74853970a7
https://doi.org/10.1145/3397481.3450689
https://doi.org/10.1145/3397481.3450689
Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems
Autor:
Eric D. Ragan, Jeremy E. Block
Publikováno v:
BELIV
Many interactive data systems combine visual representations of data with embedded algorithmic support for automation and data exploration. To effectively support transparent and explainable data systems, it is important for researchers and designers
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd80fecf11fa40d8b53ab3d6c1a7ca09
https://doi.org/10.1109/beliv51497.2020.00012
https://doi.org/10.1109/beliv51497.2020.00012
Investigating the Importance of First Impressions and Explainable AI with Interactive Video Analysis
Autor:
Jeremy E. Block, Vibhav Gogate, Tahrima Rahman, Mahsan Nourani, Chiradeep Roy, Donald R. Honeycutt, Eric D. Ragan
Publikováno v:
CHI Extended Abstracts
We present research on how the perception of intelligent systems can be influenced by early experiences of machine performance, and how explainability potentially helps users develop an accurate understanding of system capabilities. Using a custom vi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::159f5d65f3526245da79089ec9484eba
https://doi.org/10.1145/3334480.3382967
https://doi.org/10.1145/3334480.3382967
Publikováno v:
ITiCSE
Students' interest in game development often leads departments to attempt to put together a stand-alone game development course. We have used both Unity and Unreal for just such a course. Unity and Unreal are discussed here in the context of how viab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52071b63bc45423f3f34487086b888a2
https://doi.org/10.1145/3059009.3059013
https://doi.org/10.1145/3059009.3059013