Demo Data from EDBT 2026 / reviewers in the wild / expert
Kevin A. Gluck
dblp:31/4488
· DBLP profile ↗
19ranked-venue papers
6as first author
0since 2021 · last 2020
0000-0002-7969-0803ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 18 · 6 first-authorArtificial intelligence and machine learning · 16 · 4 first-authorHuman-computer interaction and ubiquitous computing · 2 · 2 first-authorSystems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 77% Performance modeling and evaluation · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems › grid computing
volunteer computing |
0.1 | 1 | 2010 | Simultaneous performance exploration and optimized search with volunteer computing · HPDC 2010 |
Performance modeling and evaluation
parameter space exploration |
0.0 | 1 | 2010 | Simultaneous performance exploration and optimized search with volunteer computing · HPDC 2010 |
Methods — techniques the papers use, named apart from their topics
volunteer computing · 0.1stochastic optimization · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Strategy Inference and Switch Detection Method Generalizes to Category Learning
Alexander Hough, Kevin A. Gluck, Michael D. Lee 0001 |
CogSci | 2 |
| 2019 | Integrating Methods to Improve Model-based Performance Prediction
Michael G. Collins, Kevin A. Gluck |
CogSci | 2 |
| 2019 | Deconvolving a Complex, Real-Life Task: Do standard lab tasks predict CPR learning and retention?
Sarah C. Maaß, Florian Sense, Michael Krusmark, Kevin A. Gluck, Hedderik van Rijn |
CogSci | 4 |
| 2018 | Using Bayesian Hierarchical Modeling and DataShop to Inform Parameter Estimation with the Predictive Performance Equation
Michael G. Collins, Kevin A. Gluck |
CogSci | 2 |
| 2017 | Using Prior Data to Inform Initial Performance Predictions of Individual Students
Michael G. Collins, Kevin A. Gluck, Matthew M. Walsh, Michael Krusmark |
CogSci | 2 |
| 2016 | Using Prior Data to Inform Model Parameters in the Predictive Performance Equation
Michael G. Collins, Kevin A. Gluck, Matthew M. Walsh, Michael Krusmark, Glenn Gunzelmann |
CogSci | 2 |
| 2016 | Instance-based Learning in Multi-cue Diagnosis
Christopher W. Myers, Kevin A. Gluck, Andrew Halsey, Jack Harris |
CogSci | 2 |
| 2015 | Communicating Cognitive Science: Improving Awareness and Understanding Among People Who are Not Ourselves
Kevin A. Gluck, Wayne D. Gray, Marsha C. Lovett, Arthur B. Markman, Jim Spohrer |
CogSci | 1 |
| 2015 | Verbal Reports Reveal Strategies in Multiple-Cue Probabilistic Inference
Matthew M. Walsh, Michael G. Collins, Kevin A. Gluck |
CogSci | 3 |
| 2014 | Computational Cognition Ideation Challenge
Kevin A. Gluck, Vladislav Daniel Veksler, Norbou Buchler, Troy D. Kelley, Paul Bello, James J. Donlon, Alonso Vera, Bob Lee |
CogSci | 1 |
| 2014 | Controlling State-Space Explosion in Chunk Learning
Vladislav Daniel Veksler, Kevin A. Gluck, Christopher W. Myers, Jack Harris, Thomas Mielke |
CogSci | 2 |
| 2014 | Using Process Measures to Track Strategy Use in Probabilistic Inference
Matthew M. Walsh, Kevin A. Gluck |
CogSci | 2 |
| 2013 | Explorations in Human and Machine Learning of Decision Trees
Kevin A. Gluck, Jack Harris, Thomas Mielke, Christopher W. Myers, Vladislav Daniel Veksler |
CogSci | 1 |
| 2013 | Making Robust Classification Decisions: Constructing and Evaluating Fast and Frugal Trees (FFTs)
Hansjörg Neth, Uwe Czienskowski, Lael J. Schooler, Kevin A. Gluck |
CogSci | 4 |
| 2012 | Annual Cognitive Modeling Competition
Kevin A. Gluck |
CogSci | 1 |
| 2012 | An Integrated Model of Associative and Reinforcement Learning
Vladislav Daniel Veksler, Christopher W. Myers, Kevin A. Gluck |
CogSci | 3 |
| 2010 | Simultaneous performance exploration and optimized search with volunteer computingabstractVolunteer computing is a powerful platform for solving complex scientific problems. [email protected] is a volunteer computing project available to the cognitive modeling community for conducting research to better understand the human mind. We are interested in optimizing search processes on volunteer resources, yet we are also interested in exploring and understanding changes in model performance across interacting, non-linear mechanisms and parameter spaces. To support both of these goals, we have developed a stochastic optimization approach and integrated it with [email protected] We tested this approach with a cognitive model on a sample parameter space, demonstrating significant decreases in computational resource utilization and search runtime, while also providing useful visual representations of performance surfaces. Future work will focus on scaling the technique to more volunteers and larger parameter spaces, as well as optimizing the performance of the search algorithm in regards to the challenges inherent with volunteer computing. L. Richard Moore Jr., Matthew Kopala, Thomas Mielke, Michael Krusmark, Kevin A. Gluck |
HPDC | 5 |
| 2000 | Broader Bandwidth in Student Modeling: What if ITS were "Eye"TS?
Kevin A. Gluck, John R. Anderson, Scott Douglass |
Intelligent Tutoring Systems | 1 |
| 1998 | Deconstructing a Computer-Based Tutor: Striving for Better Learning Efficiency in Stat Lady
Kevin A. Gluck, Valerie J. Shute, John R. Anderson, Marsha C. Lovett |
Intelligent Tutoring Systems | 1 |