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George D. Montañez

Observed names: George D Montanez, George D. Montanez, George Monta Nez, George Montanez, George Montañez, Montanez, George D., Montañez, George, Montañez, George D.
Institution: Harvey Mudd College
ORCID: 0000-0002-1333-4611
Observed ORCID: 0000-0002-1333-4611
OpenAlex ID: A5041066830
An Information-Theoretic Perspective on Overfitting and Underfitting
2020 · Daniel Bashir, George D. Montañez, et al. · Lecture notes in computer science · 67
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Virtue as a framework for the design and use of artificial intelligence
2019 · Mitchell J. Neubert, George D. Montañez · Business Horizons · 59
Cross-Device Search
2014 · George D. Montanez, Ryen W. White, et al. · ACM International Conference on Information and Knowledge Management (CIKM) · 52
Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series
2015 · George Montanez, Saeed Amizadeh, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 41
Undecidability of Underfitting in Learning Algorithms
2021 · Sonia Sehra, David Flores, et al. · 2021 2nd International Conference on Computing and Data Science (CDS) · 20
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Predicting False Positives of Protein-Protein Interaction Data by Semantic Similarity Measures§
2013 · George Montanez, Young-Rae Cho · Current Bioinformatics · 20
Limits of Transfer Learning
2020 · Jake Williams, Abel Tadesse, et al. · Lecture notes in computer science · 15
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The famine of forte: Few search problems greatly favor your algorithm
2017 · George D. Montanez · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · 14
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The Futility of Bias-Free Learning and Search
2019 · George D. Montañez, Jonathan Hayase, et al. · Lecture notes in computer science · 13
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A Unified Model of Complex Specified Information
2018 · George D Montanez · BIO-Complexity · 12
Efficient per query information extraction from a Hamming oracle
2010 · Winston Ewert, George Montanez, et al. · Southeastern Symposium on System Theory (SSST) · 10
Why Machine Learning Works
2017 · Montanez, George D. · KiltHub Repository · 9
The Bias-Expressivity Trade-off
2020 · Julius Lauw, Dominique Macias, et al. · International Conference on Agents and Artificial Intelligence (ICAART) · 7
Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation
2013 · George Montañez, Robert J. Marks II, et al. · 7
The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity
2020 · Pedro Segura, Julius Lauw, et al. · International Conference on Agents and Artificial Intelligence (ICAART) · 5
Bounding the number of favorable functions in stochastic search
2013 · George D. Montanez · IEEE Congress on Evolutionary Computation (CEC) · 5
Identifying Bias in Data Using Two-Distribution Hypothesis Tests
2022 · William Yik, Limnanthes Serafini, et al. · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · 4
The Gopher’s Gambit: Survival Advantages of Artifact-based Intention Perception
2021 · Cynthia Hom, Amani Maina-Kilaas, et al. · International Conference on Agents and Artificial Intelligence (ICAART) · 4
Vectorization of Bias in Machine Learning Algorithms
2022 · Sophie Bekerman, Eric Chen, et al. · International Conference on Agents and Artificial Intelligence (ICAART) · 3
A Probabilistic Theory of Abductive Reasoning
2021 · Nicolas Espinosa Dice, Megan Kaye, et al. · International Conference on Agents and Artificial Intelligence (ICAART) · 3
Trading Bias for Expressivity in Artificial Learning
2021 · George D. Montañez, Daniel Bashir, et al. · Lecture notes in computer science · 3
Decomposable Probability-of-Success Metrics in Algorithmic Search
2020 · Tyler Sam, Jake Williams, et al. · International Conference on Agents and Artificial Intelligence (ICAART) · 3
Assessing reliability of protein-protein interactions by gene ontology integration
2012 · George D. Montanez, Young-Rae Cho · IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) · 3
The Label Recorder Method
2022 · Kyle Rong, Aditya Khant, et al. · Lecture notes in computer science · 2
The Predator’s Purpose: Intention Perception in Simulated Agent Environments
2021 · Amani R. Maina-Kilaas, Cynthia Hom, et al. · IEEE Congress on Evolutionary Computation (CEC) · 2
Works count: 47
Citation count: 398
H-index: 10
I10-index: 11
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