PROLEARN: Towards a Prolog Interpreter that Learns. - Armand Prieditis; Jack Mostow (AAAI, 1987)

Discovering Admissible Search Heuristics by Abstracting and Optimizing. - Jack Mostow; Armand Prieditis (ML, 1989)

Discovering Admissible Heuristics by Abstracting and Optimizing: A Transformational Approach. - Jack Mostow; Armand Prieditis (IJCAI, 1989)

Generating Effective Admissible Heuristics by Abstraction and Reconstitution. - Armand Prieditis; Bhaskar Janakiraman (AAAI, 1993)

The Expected Length of a Shortest Path. - Robert Davis; Armand Prieditis (Inf. Process. Lett., 1993)

Machine Discovery of Effective Admissible Heuristics. - Armand Prieditis (Mach. Learn., 1993)

Quantitatively Relating Abstractness to the Accuracy of Admissible Heuristics. - Armand Prieditis; Robert Davis (Artif. Intell., 1995)

Adding upper-bound pruning to IDA*. - Armand Prieditis (J. Exp. Theor. Artif. Intell., 1997)

Depth-First Branch-and-Bound vs. Depth-Bounded IDA*. - Armand Prieditis (Comput. Intell., 1998)

Two-agent IDA*. - Armand Prieditis; Evan Fletcher (J. Exp. Theor. Artif. Intell., 1998)

Designing Optimal Sequential Experiments for a Bayesian Classifier. - Robert Davis; Armand Prieditis (IEEE Trans. Pattern Anal. Mach. Intell., 1999)

Mapping the Internet: Geolocating Routers by Using Machine Learning. - Armand Prieditis; Gang Chen (COM.Geo, 2013)

When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency. - Armand Prieditis; Moontae Lee (MLDM, 2013)

Lazy Overfitting Control. - Armand Prieditis; Stephanie Sapp (MLDM, 2013)

Accuracy-Based Classification EM: Combining Clustering with Prediction. - Stephanie Sapp; Armand Prieditis (MLDM, 2013)

Methodology to Create Analysis-Naive Holdout Records as well as Train and Test Records for Machine Learning Analyses in Healthcare. - Michele Bennett; Mehdi Nekouei; Armand Prieditis; Rajesh Mehta; Ewa J. Kleczyk; Karin Hayes (CoRR, 2022)