Laura E. Brown

Publication Activity (10 Years)

Years Active: 2003-2023
Publications (10 Years): 15

Top Topics

Transfer Learning

Current Practice

Relational Algebra

Top Venues

Publications

Mary E. Benjamin, Laura E. Brown, Jon Sticklen, Leo C. Ureel, Michelle Jarvie-Eggart
Engaging Novice Programmers: A Literature Review of the Effect of Code Critiquers on Programming Self-efficacy. FIE (2023)
Laura Albrant, Pradnya Pendse, Laura E. Brown, Jon Sticklen, Michelle Jarvie-Eggart, Leo C. Ureel
Work-in-Progress: Preliminary Work Introducing Automated Code Critiques in First-Year Engineering MATLAB Programming. FIE (2023)
Laura Albrant, Pradnya Pendse, Danieal Dasker, Laura E. Brown, Jon Sticklen, Michelle Jarvie-Eggart, Leo C. Ureel
Work-in-Progress: Python Code Critiquer, a Machine Learning Approach. FIE (2023)
Joseph Roy Teahen, Daniel T. Masker, Leo C. Ureel, Michelle Jarvie-Eggart, Jon Sticklen, Laura E. Brown
Extending the Usability of WebTA with Unified ASTs and Errors. FIE (2023)
Jinxiang Liu, Laura E. Brown
A Few-shot Learning Model based on a Triplet Network for the Prediction of Energy Coincident Peak Days. FLAIRS (2022)
Jinxiang Liu, Laura E. Brown
Prediction of Hour of Coincident Daily Peak Load. ISGT (2019)
Jason Hiebel, Laura E. Brown, Zhenlin Wang
Machine Learning for Fine-Grained Hardware Prefetcher Control. ICPP (2019)
Mehdi Jafari, Laura E. Brown, Lucia Gauchia
Hierarchical Bayesian Model for Probabilistic Analysis of Electric Vehicle Battery Degradation. CoRR (2019)
Jason Hiebel, Laura E. Brown, Zhenlin Wang
Constructing Dynamic Policies for Paging Mode Selection. ICPP (2018)
Laura E. Brown, Adam Feltz, Charles Wallace
Lab exercises for a discrete structures course: exploring logic and relational algebra with Alloy. ITiCSE (2018)
Abhilash Kantamneni, Laura E. Brown
An Ontology for Solar Irradiation Forecast Models. KEOD (2018)
Jing Liu, Laura E. Brown, Judith W. Dexheimer, Stephen Andrew Spooner
Detection of Weight Data-Entry Errors. AMIA (2017)
Jennifer Winikus, Laura E. Brown
Representation and incorporation of clinical information in outpatient oncology prognosis using Bayesian networks and Naïve Bayes. EIT (2016)
Michael Wollowski, Robert Selkowitz, Laura E. Brown, Ashok K. Goel, George Luger, Jim Marshall, Andrew Neel, Todd W. Neller, Peter Norvig
A Survey of Current Practice and Teaching of AI. AAAI (2016)
Todd W. Neller, Laura E. Brown, James B. Marshall, Lisa Torrey, Nate Derbinsky, Andrew A. Ward, Thomas E. Allen, Judy Goldsmith, Nahom Muluneh
Model AI Assignments 2016. AAAI (2016)
Wei Kuang, Laura E. Brown, Zhenlin Wang
Transfer Learning-Based Co-Run Scheduling for Heterogeneous Datacenters. AAAI (2015)
Wei Kuang, Laura E. Brown, Zhenlin Wang
Selective switching mechanism in virtual machines via support vector machines and transfer learning. Mach. Learn. 101 (1-3) (2015)
Abhilash Kantamneni, Laura E. Brown, Gordon G. Parker, Wayne W. Weaver
Survey of multi-agent systems for microgrid control. Eng. Appl. Artif. Intell. 45 (2015)
Wei Kuang, Laura E. Brown, Zhenlin Wang
Modeling Cross-Architecture Co-Tenancy Performance Interference. CCGRID (2015)
Todd W. Neller, Laura E. Brown, Roger L. West, James E. Heliotis, Sean Strout, Ivona Bezáková, Bikramjit Banerjee, Daniel Lucas Thompson
Model AI Assignments 2014. AAAI (2014)
Laura E. Brown, David Kauchak
EAAI-13 Preface. AAAI (2013)
Laura E. Brown, David Kauchak
Educational Advances in Artificial Intelligence. AI Mag. 34 (4) (2013)
Kaitlyn J. Bunker, Laura E. Brown, Leonard Bohmann, Gretchen Hein, Nilufer Onder, Raven R. Rebb
Perceptions and influencers affecting engineering and computer science student persistence. FIE (2013)
Laura E. Brown, Ioannis Tsamardinos, Douglas P. Hardin
To feature space and back: Identifying top-weighted features in polynomial Support Vector Machine models. Intell. Data Anal. 16 (4) (2012)
Todd W. Neller, Laura E. Brown, John Earnest, Jason Hiebel, Douglas Turnbull
Model AI Assignments 2012. EAAI (2012)
Ioannis Tsamardinos, Laura E. Brown
Bounding the False Discovery Rate in Local Bayesian Network Learning. AAAI (2008)
Laura E. Brown, Ioannis Tsamardinos
A Strategy for Making Predictions Under Manipulation. WCCI Causation and Prediction Challenge (2008)
Judith W. Dexheimer, Laura E. Brown, Jeffrey Leegon, Dominik Aronsky
Comparing Decision Support Methodologies for Identifying Asthma Exacerbations. MedInfo (2007)
Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis
The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn. 65 (1) (2006)
Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown, Constantin F. Aliferis
Generating Realistic Large Bayesian Networks by Tiling. FLAIRS Conference (2006)
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms. AAAI (2005)
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
A Novel Algorithm for Scalable and Accurate Bayesian Network Learning. MedInfo (2004)
Martha E. Pollack, Laura E. Brown, Dirk Colbry, Colleen E. McCarthy, Cheryl Orosz, Bart Peintner, Sailesh Ramakrishnan, Ioannis Tsamardinos
Autominder: an intelligent cognitive orthotic system for people with memory impairment. Robotics Auton. Syst. 44 (3-4) (2003)
Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery. METMBS (2003)