Publications

  • A. Lazar K. Wu and A. Sim "Predicting Network Traffic Using TCP Anomalies." Proceedings of the Big Data (Big Data), 2018 IEEE International Conference on. IEEE, 2018. (paper, poster)
  • A. Lazar, L. Jin, C. A. Spurlock, A. Todd, K. Wu, and A. Sim, “Data Quality Challenges with Missing Values and Mixed Types in Joint Sequence Analysis.” Proceedings of the Big Data (Big Data), 2017 IEEE International Conference on. IEEE, 2017.
  • S. Vinayak, A. Lazar and B. Sharif, "Analyzing developer sentiment in commit logs”. Proceedings of the 13th International Workshop on Mining Software Repositories (2016), May 16-18, Austin, Texas, USA, pp. 520-523, 2016.
  • A. Lazar and P. S. Fodor, “Sparsity Based Noise Removal from Low Dose Scanning Electron Microscopy Images”. Proceedings SPIE 9401, Computational Imaging XIII, 940105 (March 12, 2015); 
  • A. Lazar, S. Ritchey and B. Sharif, “Improving the Accuracy of Duplicate Bug Report Detection Using Textual Similarity Measures”. Proceedings of the 11th Working Conference on Mining Software Repositories (2014), pp. 308 – 311.
  • A. Lazar, S. Ritchey and B. Sharif, B, “Generating duplicate bug datasets”. Proceedings of the 11th Working Conference on Mining Software Repositories (2014), pp. 392–395.
  • R. Turner, M. Falcone, B. Sharif and A. Lazar, “An Eye-tracking Study Assessing the Comprehension of C++ and Python Source Code”, Symposium on Eye Tracking Research & Applications (ETRA 2014), Safety Harbor, Florida, USA, March 26-28, 2014, pp. 231-234.
  • A. Jovanovich and A. Lazar, “Comparison of Fast Learning Large-Scale Multi-Class Classification” in Proceeding of MAICS 2013: The Midwest Artificial Intelligence and Cognitive Science Conference, April 13-14, 2013, University Center at Indiana University Southeast, New Albany, IN, USA.
  • J. Curnalia and A. Lazar, “An Initial Investigation of Multi-Cyclic Training Regimen for Collaborative Filtering Models in GraphChi” in Proceeding of MAICS 2013: The Midwest Artificial Intelligence and Cognitive Science Conference, April 13-14, 2013, University Center at Indiana University Southeast, New Albany, IN, USA.
  • A. Jovanovich and A. Lazar, “Comparison of Optimization Methods for L1-regularized Logistic Regression” in Proceeding of MAICS 2012: The Midwest Artificial Intelligence and Cognitive Science Conference, 2012.
  • C. Hughes, T. Hughes and A. Lazar, “Discovering coherence and justification clusters in digital transcripts using epistemic analysis” in Proceedings of ICAIL 2011: The Thirteenth International Conference on Artificial Intelligence and Law, 2011.
  • A. Lazar and B. Shellito, “The Classification of Imbalanced Spatial Data” in Proceeding of MAICS 2011: The Midwest Artificial Intelligence and Cognitive Science Conference, 2011.
  • A. Lazar, “A Comparison of Linear Support Vector Machine Algorithms on Large Non-Sparse Datasets” in Proceedings of ICMLA’2010: The 2010 International Conference on Machine Learning and Applications, IEEE, 2010.
  • T. Hughes, C. Hughes, and A. Lazar. "Epistemic structured representation for legal transcript analysis." Advances in Computer and Information Sciences and Engineering. Springer Netherlands, 2008. 101-107.
  • A. Lazar, “Engaged Learning in a Discrete Mathematics Course” accepted at the Consortium for Computer Science in Colleges Midwest – CCSC-MW 2007, 28-29 September 2007, Miami University, Hamilton, OH.
  • A. Lazar and B. Shellito, “Classification in GIS using Support Vector Machines” in Encyclopedia of Geoinformatics, Information Science Publishing (Idea Group Inc.) 2006.
  • A. Lazar and R. Zaremba, “Support Vector Machines Optimization - An Income Prediction Study” in Proceedings of ICCGI’2006: International Multi-Conference on Computing in the Global Information Technology -Challenges for the Next Generation of IT & C, IEEE, August 1-3, 2006 - Bucharest, Romania.
  • K. Duda, A. Lazar and L. Popio, “Enrollment Differences by Gender in Computer Science, Computer Information Systems, and Information Technology” in Proceedings of Research on Women in Education 31st Annual Fall Conference, 2005.
  • A. Lazar and B. Shellito, “Comparing Machine Learning Classification Schemes – a GIS Approach” in Proceedings of ICMLA’2005: The 2005 International Conference on Machine Learning and Applications, IEEE, 2005.
  • B. Shellito and A. Lazar, “Applying Support Vector Machines and GIS to Urban Pattern Recognition,” in Papers of the Applied Geography Conferences, volume 28, 2005. 
  • A. Lazar, “Income Prediction via Support Vector Machines” in Proceedings of ICMLA’2004: The 2004 International Conference on Machine Learning and Applications, IEEE, 2004
  • A. Lazar, “An Overview of Heuristic Knowledge Discovery for Large Data Sets Using Genetic Algorithms and Rough Sets” in Encyclopedia of Information Science and Information Technology, Information Science Publishing (Idea Group Inc.) 2005
  • A. Lazar, D. Chavalarias, T.K. Ahn, “Endogenous Network Formation and the Evolution of Preferences” Social Agents: Ecology, Exchange & Evolution (Agent 2002), Chicago, October 11-12, 2002
  • R.G. Reynolds, A. Lazar, “Agent-based Simulation of the Evolution of Archaic States” Agent 2002 Social Agents: Ecology, Exchange & Evolution (Agent 2002), Chicago, October 11-12, 2002
  • R.G. Reynolds, A. Lazar, “Computational Framework for Modeling the Dynamic Evolution of Large-Scale Multi-agent Organizations” Computational Analysis of Social and Organizational Systems (CASOS 2002), Carnegie Melon University, Pittsburgh, Pa, June 21-23, 2002
  • R.G. Reynolds, A. Lazar, “Simulating the Evolution of Archaic States” 2002 Congress on Evolutionary Computation (WCII 2002), Hilton Hawaiian Village, Honolulu, HI, May 12-17, 2002.
  • R.G. Reynolds, A. Lazar, "Computational Framework for Modeling the Dynamic Evolution of Large-scale Multi-agent Organizations", at SPIE's 16th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls, 1-5 April 2002, Orlando, Florida, USA.
  • A. Lazar and R.G. Reynolds, “Evolution-based Learning of Ontological Knowledge for a Large-scale Multi-agent Simulation”, at The Fourth International Workshop on Frontiers in Evolutionary Algorithms (FEA 2002), Research Triangle Park, North Carolina, USA, March 8-13, 2002.
  • A. Lazar and R.G. Reynolds, "Heuristic Knowledge Discover for Archaeological Data Using Cultural Algorithms and Rough Sets", in Vol. 2: Heuristics and Optimization for Knowledge Discovery (ed. Ruhul A. Sarker, Hussein A. Abbass, and Charles S. Newton) by Idea Group Publishing, USA, 2002.
  • A. Lazar and I.K. Sethi, "Decision rule extraction from trained neural networks using rough sets'', in Intelligent Engineering Systems Through Artificial Neural Networks (C.H. Dagli, A.L. Buczak, and J. Ghosh, eds.), vol. 9, (New York, NY), pp. 493-498, ASME Press, Nov. 1999.