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ORCIDGeorge D. Montañez
Person information
- affiliation: Harvey Mudd College, Department of Computer Science, Claremont, CA, USA
- affiliation (PhD): Carnegie Mellon University, Pittsburgh, PA, USA
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2020 – today
- 2024
[c31]Milo Knell, Sahil Rane, Forrest Bicker, Tiger Che, Alan Wu, George D. Montañez:
From Targets to Rewards: Continuous Target Sets in the Algorithmic Search Framework. ICAART (3) 2024: 558-567- 2023
- [c30]Cynthia Hom, William Yik, George D. Montañez:
Finite-Sample Bounds for Two-Distribution Hypothesis Tests. DSAA 2023: 1-11 - 2022
- [c29]William Yik
, Limnanthes Serafini, Timothy Lindsey, George D. Montañez:
Identifying Bias in Data Using Two-Distribution Hypothesis Tests. AIES 2022: 831-844 - [c28]Jiayi Zhao, Anshul Kamath, Nick Grisanti, George D. Montañez:
Generating the Gopher's Grounds: Form, Function, Order, and Alignment. ICAART (Revised Selected Paper 2022: 143-168 - [c27]Sophie Bekerman, Eric Chen, Lily Lin, George D. Montañez:
Vectorization of Bias in Machine Learning Algorithms. ICAART (2) 2022: 354-365 - [c26]Anshul Kamath, Jiayi Zhao, Nick Grisanti, George D. Montañez:
The Gopher Grounds: Testing the Link between Structure and Function in Simple Machines. ICAART (2) 2022: 528-540 - [c25]Ramya Ramalingam, Nicolas A. Espinosa Dice, Megan L. Kaye, George D. Montañez:
Bounding Generalization Error Through Bias and Capacity. IJCNN 2022: 1-8 - 2021
- [c24]Amani R. Maina-Kilaas, Cynthia Hom, Kevin Ginta, George D. Montañez:
The Predator's Purpose: Intention Perception in Simulated Agent Environments. CEC 2021: 1619-1626 - [c23]Amani R. Maina-Kilaas, George D. Montañez, Cynthia Hom, Kevin Ginta, Cindy Lay:
The Hero's Dilemma: Survival Advantages of Intention Perception in Virtual Agent Games. CoG 2021: 1-8 - [c22]Cynthia Hom, Amani R. Maina-Kilaas, Kevin Ginta, Cindy Lay, George D. Montañez:
The Gopher's Gambit: Survival Advantages of Artifact-based Intention Perception. ICAART (1) 2021: 205-215 - [c21]Nicolas A. Espinosa Dice, Megan L. Kaye, Hana Ahmed, George D. Montañez:
A Probabilistic Theory of Abductive Reasoning. ICAART (2) 2021: 562-571 - [c20]Kyle Rong, Aditya Khant, David Flores, George D. Montañez:
The Label Recorder Method - Testing the Memorization Capacity of Machine Learning Models. LOD 2021: 581-595 - [c19]Eric M. Weiner, George D. Montañez, Aaron Trujillo, Abtin Molavi:
Hyperparameter Choice as Search Bias in AlphaZero. SMC 2021: 2389-2394 - [i10]Sonia Sehra, David Flores, George D. Montañez:
Undecidability of Underfitting in Learning Algorithms. CoRR abs/2102.02850 (2021) - [i9]George D. Montañez:
Permutation Encoding for Text Steganography: A Short Tutorial. CoRR abs/2104.03881 (2021) - 2020
- [c18]Daniel Bashir, George D. Montañez, Sonia Sehra, Pedro Sandoval Segura, Julius Lauw:
An Information-Theoretic Perspective on Overfitting and Underfitting. Australasian Conference on Artificial Intelligence 2020: 347-358 - [c17]George D. Montañez, Laina Sanders, Howard Deshong:
Minimal Complexity Requirements for Proteins and Other Combinatorial Recognition Systems. BIOINFORMATICS 2020: 71-78 - [c16]Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti, George D. Montañez:
The Bias-Expressivity Trade-off. ICAART (2) 2020: 141-150 - [c15]George D. Montañez, Daniel Bashir, Julius Lauw:
Trading Bias for Expressivity in Artificial Learning. ICAART (Revised Selected Papers) 2020: 332-353 - [c14]Tyler Sam, Jake Williams, Abel Tadesse, Huey Sun, George D. Montañez:
Decomposable Probability-of-Success Metrics in Algorithmic Search. ICAART (2) 2020: 785-792 - [c13]Pedro Sandoval Segura, Julius Lauw, Daniel Bashir, Kinjal Shah, Sonia Sehra, Dominique Macias, George D. Montañez:
The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity. ICAART (2) 2020: 980-986 - [c12]Jake Williams, Abel Tadesse, Tyler Sam, Huey Sun, George D. Montañez:
Limits of Transfer Learning. LOD (2) 2020: 382-393 - [c11]Jarred Allen, Cindy Lay, George D. Montañez:
A Castro Consensus: Understanding the Role of Dependence in Consensus Formation. TTO 2020: 12-20 - [i8]Tyler Sam, Jake Williams, Abel Tadesse, Huey Sun, George D. Montañez:
Decomposable Probability-of-Success Metrics in Algorithmic Search. CoRR abs/2001.00742 (2020) - [i7]Jake Williams, Abel Tadesse, Tyler Sam, Huey Sun, George D. Montañez:
Limits of Transfer Learning. CoRR abs/2006.12694 (2020) - [i6]Daniel Bashir, George D. Montañez, Sonia Sehra, Pedro Sandoval Segura, Julius Lauw:
An Information-Theoretic Perspective on Overfitting and Underfitting. CoRR abs/2010.06076 (2020)
2010 – 2019
- 2019
- [c10]George D. Montañez, Jonathan Hayase, Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti:
The Futility of Bias-Free Learning and Search. Australasian Conference on Artificial Intelligence 2019: 277-288 - [i5]George D. Montañez, Jonathan Hayase, Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti:
The Futility of Bias-Free Learning and Search. CoRR abs/1907.06010 (2019) - [i4]Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti, George D. Montañez:
The Bias-Expressivity Trade-off. CoRR abs/1911.04964 (2019) - [i3]Pedro Sandoval Segura, Julius Lauw, Daniel Bashir, Kinjal Shah, Sonia Sehra, Dominique Macias, George D. Montañez:
The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity. CoRR abs/1912.10597 (2019) - 2017
- [c9]George D. Montañez, Cosma Rohilla Shalizi:
The LICORS cabinet: Nonparametric light cone methods for spatio-temporal modeling. IJCNN 2017: 2811-2819 - [c8]George D. Montañez:
Estimating the Prevalence of Religious Content in Intelligent Design Social Media. IRI 2017: 462-470 - [c7]George D. Montañez:
The famine of forte: Few search problems greatly favor your algorithm. SMC 2017: 477-482 - 2016
- [b1]George D. Montañez:
Why Machine Learning Works. Carnegie Mellon University, USA, 2016 - [c6]George D. Montañez:
Detecting Intelligence - The Turing Test and Other Design Detection Methodologies. ICAART (2) 2016: 517-523 - [i2]George D. Montañez:
The Famine of Forte: Few Search Problems Greatly Favor Your Algorithm. CoRR abs/1609.08913 (2016) - 2015
- [c5]George D. Montañez, Saeed Amizadeh, Nikolay Laptev:
Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series. AAAI 2015: 1819-1825 - [i1]George D. Montañez, Cosma Rohilla Shalizi:
The LICORS Cabinet: Nonparametric Algorithms for Spatio-temporal Prediction. CoRR abs/1506.02686 (2015) - 2014
- [c4]George D. Montañez, Ryen W. White, Xiao Huang:
Cross-Device Search. CIKM 2014: 1669-1678 - 2013
- [c3]George D. Montañez:
Information transmission through genetic algorithm fitness maps. IEEE Congress on Evolutionary Computation 2013: 756-763 - [c2]George D. Montañez:
Bounding the number of favorable functions in stochastic search. IEEE Congress on Evolutionary Computation 2013: 3019-3026 - 2012
- [c1]George D. Montañez, Young-Rae Cho:
Assessing reliability of protein-protein interactions by gene ontology integration. CIBCB 2012: 21-27
Coauthor Index
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