| Cross-device search GD Montanez, RW White, X Huang Proceedings of the 23rd ACM international conference on conference on …, 2014 | 77 | 2014 |
| An information-theoretic perspective on overfitting and underfitting D Bashir, GD Montañez, S Sehra, PS Segura, J Lauw AI 2020: Advances in Artificial Intelligence: 33rd Australasian Joint …, 2020 | 73 | 2020 |
| Virtue as a framework for the design and use of artificial intelligence MJ Neubert, GD Montañez Business Horizons 63 (2), 195-204, 2020 | 67 | 2020 |
| Inertial hidden markov models: Modeling change in multivariate time series G Montanez, S Amizadeh, N Laptev Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 64 | 2015 |
| Predicting False Positives of Protein-Protein Interaction Data by Semantic Similarity Measures G Montanez, YR Cho Current Bioinformatics 8 (3), 339-346, 2013 | 23 | 2013 |
| The famine of forte: Few search problems greatly favor your algorithm GD Montanez 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017 | 22 | 2017 |
| Why machine learning works GD Montanez URL https://www. cs. cmu. edu/~ gmontane/montanez_dissertation. pdf, 2017 | 20 | 2017 |
| Efficient per query information extraction from a hamming oracle W Ewert, G Montanez, WA Dembski, RJ Marks 2010 42nd Southeastern Symposium on System Theory (SSST), 290-297, 2010 | 19 | 2010 |
| A unified model of complex specified information GD Montañez Bio-Complexity 2018, 2018 | 18 | 2018 |
| Multiple overlapping genetic codes profoundly reduce the probability of beneficial mutation G Montañez, RJ Marks II, J Fernandez, JC Sanford Biological Information: New Perspectives, 139-167, 2013 | 18 | 2013 |
| Undecidability of underfitting in learning algorithms S Sehra, D Flores, GD Montañez 2021 2nd International Conference on Computing and Data Science (CDS), 591-594, 2021 | 17 | 2021 |
| A vivisection of the ev computer organism: identifying sources of active information G Montañez, W Ewert, WA Dembski, RJ Marks II Bio-Complexity 2010, 2010 | 17 | 2010 |
| Limits of transfer learning J Williams, A Tadesse, T Sam, H Sun, GD Montañez Machine Learning, Optimization, and Data Science: 6th International …, 2020 | 16 | 2020 |
| The futility of bias-free learning and search GD Montañez, J Hayase, J Lauw, D Macias, A Trikha, J Vendemiatti Australasian Joint Conference on Artificial Intelligence, 277-288, 2019 | 14 | 2019 |
| The Bias-Expressivity Trade-off J Lauw, D Macias, A Trikha, J Vendemiatti, GD Montanez Proceedings of the 12th International Conference on Agents and Artificial …, 2019 | 8 | 2019 |
| Bounding the number of favorable functions in stochastic search GD Montanez 2013 IEEE Congress on evolutionary computation, 3019-3026, 2013 | 8 | 2013 |
| The Gopher’s Gambit: Survival Advantages of Artifact-based Intention Perception [The Gopher’s Gambit: Survival Advantages of Artifact-based Intention Perception] C Hom, A Maina-Kilaas, K Ginta, C Lay, G Montañez Proceedings of the 13th International Conference on Agents and Artificial …, 2021 | 7 | 2021 |
| The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity PS Segura, J Lauw, D Bashir, K Shah, S Sehra, D Macias, G Montanez Proceedings of the 12th International Conference on Agents and Artificial …, 2019 | 7 | 2019 |
| Identifying bias in data using two-distribution hypothesis tests W Yik, L Serafini, T Lindsey, GD Montañez Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 831-844, 2022 | 5 | 2022 |
| Trading Bias for Expressivity in Artificial Learning GD Montañez, D Bashir, J Lauw Agents and Artificial Intelligence: 12th International Conference, ICAART …, 2021 | 5 | 2021 |
Julius LauwBestätigte E-Mail-Adresse bei g.hmc.edu
