2017

Piyush Sharma and Gary Holness. L2-norm Transformation for Improving k-means Clustering: Finding A Suitable Model By Range Transformation for Novel Data Analysis International Journal of Data Science and Analytics, June 2017, Volume 3, Issue 4, pp 247-266. doi:10.1007/s41060-017-0054-1
Janelle Boyd and Gary Holness. Understanding Social Queues to Participate in a Turn-Taking Interaction with Autistic Children Academic and Research Leadership Symposium, National Society of Black Engneers 43rd Annual Convention, Kansas City, MO, March 29th - April 2nd, 2017 poster

2016

Piyush Sharma and Gary Holness. Dialation of Chisini Jensen-Shannon Divergence 3rd IEEE International Conference Data Science and Advanced Analytics (DSAA 2016), October 2016

2015

Piyush Sharma and Gary Holness and Yuri Markushin and Noureddine Melikechi. A Family of Chisini Mean Based Jensen-Shannon Divergence Kernels 14th IEEE International Conference on Machine Learning and Applications (ICMLA 2015), December 2015
Piyush Sharma and Gary Holness and Sivakumar Poopalasingam and Yuri Markushin and Noureddine Melikechi. Investigating Manifold Neighborhood size for Nonlinear Analysis of LIBS Amino Acid Spectra 24th International Conference on Software Engineering and Data Engineering (SEDE 2015), October 12-14, 2015 (individual paper available)
Piyush Sharma and Gary Holness and Poopalasingam Sivakumar and Yuri Markushin and Noureddine Melikechi. Analysis of LIBS Amino Acid Spectra and the Impact of Neighborhood Size on the efficacy of nonlinear analysis 1st Delaware Optics Symposium (DOS 2015), poster October 8-9, 2015
Gary Holness and Leon Hunter. A Prototype Distributed Framework for Identification and Alerting for Medical Events in Home Care Technology Interface International Journal, Volume 15, Number 2., Spring/Summer 2015
Janelle Boyd and Gary Holness. A Framework for Perceptual Processing in Autonomous Wheelchairs poster Emerging Researchers National Conference in STEM (ERN 2015), February 2015

2014

David D. Pokrajac and Poopalasingam Sivakumar and Yuri Markushin and Daniela Milovic and Mukti Ranai and Gary Holness and Jinjie Liu and Noureddine Melikechi. Towards Optimal Classifier of Spectroscopy Data Proceedings of the 1st International Conference onElectrical, Electronic, and Computer Engineering (icETRAN)Vrnjacka Banja, Serbia, June 2014.
Gary Holness and Leon Hunter. A Prototype Distributed Framework for Identification and Alerting for Medical Events in Home Care Proceedings of the 4th IAJC/ISAM Joint International Conference, Sept. 2014.
Tevin Brown and Gary Holness. Improving LIBS Analysis using Nonlinear Dimensionality Reduction. poster Summer Research Symposium, Delaware State University , July 2014. poster
Leon Hunter and Gary Holness. Identifying Precursor Warnings of Potentially Fatal Afflictions via Web Service . poster Emerging Researchers National Conference in STEM (ERN 2014), February. 2014. poster

2013

Gabriel Calderon Ortiz and Gary Holness. Using Robots to Improve Socialization Skills of Autistic Children. poster Summer Research Symposium, Delaware State University, July 2013.
Leon Hunter and Gary Holness. Identifying Precursor Warnings of Potentially Fatal Afflictions via Web Service. poster Summer Research Symposium, Delaware State University, July 2013.
Tevin Brown and Gary Holness. Linkage Analysis of LIBS Protein Spectra. poster Summer Research Symposium, Delaware State University, July 2013.

2012

Paul Biancaniello, Gary Holness, Jonathan Darvill, Matt Craven, Patrick Lardieri. AIR: A Framework for Adaptive Immune Response for Cyber Defense. Journal of Intelligence Community Research and Development, permanently available on Intelink (available here at Lockheed Martin), 25 May 2012.

2010

Eric Eaton, Gary Holness, and Daniel McFarlane. Interactive Learning using Manifold Geometry. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), pp. 437–443, AAAI Press, July 11--15 2010.

2009

Gary Holness, and Paul Utgoff. Training Ensembles Using Max-Entropy Error Diversity, In Proceedings of the 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, pp. 202–209, AIP Conferenc Proceedings, Dec 8, 2009.
Eric Eaton, Gary Holness, and Daniel McFarlane. Interactive Learning using Manifold Geometry. In Proceedings of the AAAI Fall Symposium on Manifold Learning and Its Applications (AAAI Technical Report FS-09-04), pp. 10–17, AAAI Press, November 5--7 2009.
Superseded by the AAAI-10 conference paper Interactive Learning using Manifold Geometry.

2008

Gary Holness. A Statistical Approach to Improving Accuracy in Classifier Ensembles. PhD Thesis, University of Massachusetts Amherst, September 2008.

2007

G. Holness. A Direct Measure for the Efficacy of Bayesian Network Structures Learned from Data. In P. Perner(Ed.), Machine Learning and Data Mining in Pattern Recognition, LNAI 4571, Springer Verlag, Heidelberg, 2007, pp. 601-615.
Gary Holness. Markov Blanket Retrieval: An Approach for Measuring the Efficacy of Bayesian Network Structures Learned from Data. Technical Report QLI-TR-2007-04, Quantum Leap Innovations, January 2007.
Gary Holness. Heureka Technologies for Invensys-Pathfinder. Technical Report QLI-TR-2007-09, Quantum Leap Innovations, May 2007.
Gary Holness. Markov Chain Monte-Carlo Simulation of Incidence of Infection and Recovery in SIR Disease Modeling. Technical Report QLI-TR-2007-10, Quantum Leap Innovations, July 2007.

2005

M. Sieracki, E. Riseman, W. Balsh, M. Benfield, A. Hanson, C. Pilskaln, H Schultz, C. Sieracki, P. Utgoff, M. Blaschko, G. Holness, M. Mattar, D. Lisin, and B. Tupper. Automatic Classification of Plankton from Digital Images. ASLO Aquatic Sciences Meeting, Salt Lake City, Utah, Februrary 2005.
M. Blaschko and G. Holness and M. Mattar and D. Lisin and P. Utgoff and A. Hanson and H. Schultz and E. Riseman and M. Sieracki and W. Balch and B. Tupper. Automatic In Situ Identification of Plankton. ASLO Aquatic Sciences Meeting, Salt Lake City, Utah, Februrary 2005.
Gary Holness. Model Checking a Real-Time Foveate Controller Using Timed Automata. TR-05-56, University of Massachusetts-Amherst, Amherst, MA, 2005.

2004

Gary Holness and Kimerly N. Martin. Towards a Machine Learning DJ: First Experiments. Technical Report TR-04-01, Department of Computer Science, University of Massachusetts-Amherst, 2004.

2003

Gary Holness and Rod Grupen and Jack Wileden. Context Recovery Through Meta-Sensing. Synthesis Project (Unpublished Work), Department of Computer Science, University of Massachusetts-Amherst, 2003.

2001

Gary Holness and Deepak Karuppiah and Subramania Uppala and Sai Chandu Ravela and Rod Grupen. A Service Paradigm for Reconfigurable Agents. Prodeedings of 2nd Workshop on Infrastructure for Agents, MAS, and Scalable MAS (Agents 2001), Montreal, Canada, 2001.

2000

Deepak Karuppiah and Patrick Deegan and Elizeth Araujo and Yunlei Yang and Gary Holness and Zhigang Zhu and Barbara Lerner and Rod Grupen and Ed Riseman. Software Mode Changes for Continuous Motion Tracking. Proceedings of the International Workshop on Self-Adaptive Software (IWSAS2000), Oxford, England, 2000.
Jim Waldo and The Jini Technology Team The Jini Specifications Second Edition. Chapter: The Jini Event Mailbox, 2000.