Brandon M. Malone

Orcid: 0000-0002-7027-3157

Affiliations:
  • NEC Laboratories Europe, Heidelberg, Germany
  • Helsinki Institute for Information Technology, Department of Computer Science, Finland
  • Mississippi State University, Department of Computer Science and Engineering, MS, USA
  • Tennessee Technological University, Cookeville, TN, USA


According to our database1, Brandon M. Malone authored at least 29 papers between 2008 and 2021.

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Timeline

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Bibliography

2021
BERTMHC: improved MHC-peptide class II interaction prediction with transformer and multiple instance learning.
Bioinform., November, 2021

2019
Early Detection of Infection Chains & Outbreaks: Use Case Infection Control.
Proceedings of the ICT for Health Science Research - Proceedings of the EFMI 2019 Special Topic Conference, 2019

2018
Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction.
Mach. Learn., 2018

Learning Representations of Missing Data for Predicting Patient Outcomes.
CoRR, 2018

Knowledge Graph Completion to Predict Polypharmacy Side Effects.
Proceedings of the Data Integration in the Life Sciences - 13th International Conference, 2018

2017
Duplicate Detection for Bayesian Network Structure Learning.
New Gener. Comput., 2017

AS-ASL: Algorithm Selection with Auto-sklearn.
Proceedings of the Open Algorithm Selection Challenge 2017, 2017

Advanced Methodologies for Bayesian Networks 2017: Preface.
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017

2015
Impact of Learning Strategies on the Quality of Bayesian Networks: An Empirical Evaluation.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Hashing-Based Hybrid Duplicate Detection for Bayesian Network Structure Learning.
Proceedings of the Advanced Methodologies for Bayesian Networks, 2015

MaxSAT-Based Cutting Planes for Learning Graphical Models.
Proceedings of the Integration of AI and OR Techniques in Constraint Programming, 2015

2014
Finding Optimal Bayesian Network Structures with Constraints Learned from Data.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Portfolio-Based Selection of Robust Dynamic Loop Scheduling Algorithms Using Machine Learning.
Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Predicting the Hardness of Learning Bayesian Networks.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Tightening Bounds for Bayesian Network Structure Learning.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Learning Optimal Bayesian Networks: A Shortest Path Perspective.
J. Artif. Intell. Res., 2013

Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Predicting the Flexibility of Dynamic Loop Scheduling Using an Artificial Neural Network.
Proceedings of the IEEE 12th International Symposium on Parallel and Distributed Computing, 2013

A Depth-First Branch and Bound Algorithm for Learning Optimal Bayesian Networks.
Proceedings of the Graph Structures for Knowledge Representation and Reasoning, 2013

2012
Empirical evaluation of scoring functions for Bayesian network model selection.
BMC Bioinform., 2012

An Improved Admissible Heuristic for Learning Optimal Bayesian Networks.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011
The Proteogenomic Mapping Tool.
BMC Bioinform., 2011

Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound Search.
Proceedings of the UAI 2011, 2011

Learning Optimal Bayesian Networks Using A* Search.
Proceedings of the IJCAI 2011, 2011

Memory-Efficient Dynamic Programming for Learning Optimal Bayesian Networks.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2009
Integrating phenotype and gene expression data for predicting gene function.
BMC Bioinform., 2009

2008
Tracking requirements and threats for secure software development.
Proceedings of the 46th Annual Southeast Regional Conference, 2008

Utilizing smart cards for authentication and compliance tracking in a diabetes case management system.
Proceedings of the 46th Annual Southeast Regional Conference, 2008


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