Publications

2023 Zhao, J, Kamath, A, Grisanti, N, Montañez G, “Generating the Gopher’s Grounds: Form, Function, Order, and Alignment.” In Agents and Artificial Intelligence: 14th International Conference (ICAART 2022), Virtual Event, February 3-5, 2022. Revised Selected Papers (pp. 143-168). Lecture Notes in Computer Science doi:10.1007/978-3-031-22953-4_7. PDF Cite

2022 Yik W, Serafini L, Lindsey T, Montañez G, “Identifying Bias in Data Using Two-Distribution Hypothesis Tests.” 2022 AAAI/ACM Conference on AI, Ethics, and Society (AAAI/ACM AIES 2022), Oxford, United Kingdom, August 1-3, 2022. pp. 831-844, doi:10.1145/3514094.3534169. PDF Cite

2022 Ramalingam R, Espinosa Dice N, Kaye M, Montañez G, “Bounding Generalization Error Through Bias and Capacity.” 2022 International Joint Conference on Neural Networks (IJCNN 2022), Padua, Italy, July 18-23, 2022. pp. 1-8, doi:10.1109/IJCNN55064.2022.9891905. PDF Cite

2022 Kamath A, Zhao J, Grisanti N, Montañez G, “The Gopher Grounds: Testing the Link between Structure and Function in Simple Machines.” 14th International Conference on Agents and Artificial Intelligence (ICAART 2022), Online, Feb 3-5, 2022. PDF Cite

2022 Bekerman S, Chen E, Lin L, Montañez G, “Vectorization of Bias in Machine Learning Algorithms.” 14th International Conference on Agents and Artificial Intelligence (ICAART 2022), Online, Feb 3-5, 2022. PDF Cite

2021 Weiner E, Montañez G, Trujillo A, Molavi A, “Hyperparameter Choice as Search Bias in AlphaZero.” IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2021), Online, October 17-20, 2021. PDF Cite

2021 Rong K, Khant A, Flores D, Montañez G, “The Label Recorder Method: Testing the Memorization Capacity of Machine Learning Models.” The Seventh International Conference on Machine Learning, Optimization, and Data Science (LOD 2021), October 4-8, 2021. PDF Cite

2021 Maina-Kilaas A, Montañez G, Hom C, Ginta K, Lay C, “The Hero's Dilemma: Survival Advantages of Intention Perception in Virtual Agent Games.” 2021 IEEE Conference on Games (IEEE CoG 2021), Online, August 17-20, 2021. PDF Cite

2021 Maina-Kilaas A, Hom C, Ginta K, Montañez G, “The Predator's Purpose: Intention Perception in Simulated Agent Environments.” Evolutionary Computation (CEC), 2021 IEEE Congress on, Online, June 28-July 1, 2021. PDF Cite

2021 Montañez G, Bashir D, Lauw J, “Trading Bias for Expressivity in Artificial Learning.” In: Rocha A.P., Steels L., van den Herik J. (eds) Agents and Artificial Intelligence. ICAART 2020. Lecture Notes in Computer Science, vol 12613. Springer, Cham. https://doi.org/10.1007/978-3-030-71158-0_16 . PDF Cite

2021 Sehra S, Flores D, Montañez G, “Undecidability of Underfitting in Learning Algorithms.” 2nd International Conference on Computing and Data Science (CONF-CDS 2021), Online (Virtual Conference), Jan 25-28, 2021. PDF Cite

2021 Espinosa Dice N, Kaye M, Ahmed H, Montañez G, “A Probabilistic Theory of Abductive Reasoning.” 13th International Conference on Agents and Artificial Intelligence (ICAART 2021), Online, Feb 4-6, 2021. PDF Cite

2021 Hom C, Maina-Kilaas A, Ginta K, Lay C, Montañez G, “The Gopher's Gambit: Survival Advantages of Artifact-Based Intention Perception.” 13th International Conference on Agents and Artificial Intelligence (ICAART 2021), Online, Feb 4-6, 2021. PDF Cite

2020 Allen J, Lay C, Montañez G, “A Castro Consensus: Understanding the Role of Dependence in Consensus Formation” Conference on Truth and Trust Online (TTO 2020), October 16-17, 2020. PDF Cite

2020 Bashir D, Montañez G, Sehra S, Sandoval Segura P, Lauw J, “An Information-Theoretic Perspective on Overfitting and Underfitting” Australasian Joint Conference on Artificial Intelligence (AJCAI 2020), November 29-30, 2020. PDF Cite

2020 Williams J, Tadesse A, Sam T, Sun H, Montañez G, “Limits of Transfer Learning” The Sixth International Conference on Machine Learning, Optimization, and Data Science (LOD 2020), July 19-23, 2020. PDF Cite

2020 Sam T, Williams J, Tadesse A, Sun H, Montañez G, “Decomposable Probability-of-Success Metrics in Algorithmic Search.” 12th International Conference on Agents and Artificial Intelligence (ICAART 2020), 2020. PDF Cite

2020 Lauw J, Macias D, Trikha A, Vendemiatti J, Montañez G, “The Bias-Expressivity Trade-off.” 12th International Conference on Agents and Artificial Intelligence (ICAART 2020), 2020.
(16% acceptance rate for full papers.)
—Awarded Best Paper PDF Cite

2020 Sandoval Segura P, Lauw J, Bashir D, Shah K, Sehra S, Macias D, Montañez G, “The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity.” 12th International Conference on Agents and Artificial Intelligence (ICAART 2020), 2020. PDF Cite

2020 Montañez G, Sanders L, Deshong H, “Minimal Complexity Requirements for Proteins and Other Combinatorial Recognition Systems.” 11th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2020), 2020. PDF Cite

2019 Neubert M, Montañez G, “Virtue as a Framework for the Design and Use of Artificial Intelligence.” Business Horizons, 2019. ISSN 0007-6813. PDF Cite

2019 Montañez G, Hayase J, Lauw J, Macias D, Trikha A, Vendemiatti J, “The Futility of Bias-Free Learning and Search.” 32nd Australasian Joint Conference on Artificial Intelligence (AI 2019), 2019. 277–288 PDF Cite

2018 Montañez G, “A Unified Model of Complex Specified Information.” BIO-Complexity, 2018(4). 1–26. doi:10.5048/BIO-C.2018.4 PDF Cite

2017 Montañez G, “The Famine of Forte: Few Search Problems Greatly Favor Your Algorithm.” IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2017), 2017. 477–482
—Awarded Best Student Paper PDF Cite

2017 Montañez G, “Estimating the Prevalence of Religious Content in Intelligent Design Social Media” IEEE International Conference on Information Reuse and Integration (IEEE IRI 2017), 2017. 462–470. PDF Cite

2017 Montañez G, Shalizi CR, “The LICORS Cabinet: Nonparametric Light Cone Methods for Spatio-Temporal Modeling.” International Joint Conference on Neural Networks (IJCNN 2017), 2017.
—Awarded INNS/Intel Best Student Paper
—Awarded Best Poster PDF Cite

2016 Montañez G, “Detecting Intelligence: The Turing Test and Other Design Detection Methodologies.” 8th International Conference on Agents and Artificial Intelligence (ICAART 2016), 2016. 517-523. PDF Cite

2015 Montañez G, Amizadeh S & Laptev N, “Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series.” AAAI Conference on Artificial Intelligence (AAAI 2015), 2015. 1819-1825 PDF Cite

2014 Montañez G, White RW & Huang X, “Cross-Device Search.” In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management (CIKM 2014) (pp. 1669-1678). ACM.
—Awarded Best Paper PDF Cite

2013 Montañez G, Cho YR, “Predicting False Positives of Protein-Protein Interaction Data by Semantic Similarity Measures.” Current Bioinformatics (Journal version of CIBCB 2012 paper). PDF Cite

2013 Montañez G, “Information Transmission through Genetic Algorithm Fitness Maps.” Evolutionary Computation (CEC), 2013 IEEE Congress on, 2013. 756-763  PDF Cite

2013 Montañez G, “Bounding the Number of Favorable Functions in Stochastic Search.” Evolutionary Computation (CEC), 2013 IEEE Congress on, 2013. 3019-3026 PDF Cite

2013 Montañez G, Marks II RJ, Fernandez J & Sanford JC, “Multiple overlapping genetic codes profoundly reduce the probability of beneficial mutation.” Biological Information—New Perspectives. World Scientific, Singapore (2013): 139-167. PDF Cite

2012 Montañez G, Cho YR, “Assessing Reliability of Protein-Protein Interactions by Gene Ontology Integration.” Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2012), 2012 IEEE Symposium on PDF Cite

2010 Montañez G, Ewert W, Dembski WA & Marks II RJ, “A vivisection of the ev computer organism: Identifying sources of active information.” BIO-Complexity 2010(3):1-6. PDF Cite

2010 Ewert W, Montañez G, Dembski WA & Marks II RJ, “Efficient per query information extraction from a hamming oracle.” 42nd Southeastern Symposium on System Theory (SSST 2010), 290-297 PDF Cite