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Journal Articles
- 2023
[j5]Julia Cluceru, Janine M. Lupo, Yannet Interian, Riley Bove, Jason C. Crane
:
Improving the Automatic Classification of Brain MRI Acquisition Contrast with Machine Learning. J. Digit. Imaging 36(1): 289-305 (2023)- 2022
- [j4]Gilmer Valdes, Yannet Interian, Efstathios D. Gennatas, Mark J. van der Laan:
The Conditional Super Learner. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 10236-10243 (2022) - 2021
- [j3]Ményssa Cherifa, Yannet Interian, Alice Blet, Matthieu Resche-Rigon, Romain Pirracchio:
The Physiological Deep Learner: First application of multitask deep learning to predict hypotension in critically ill patients. Artif. Intell. Medicine 118: 102118 (2021) - 2013
- [j2]Tom Broxton, Yannet Interian, Jon Vaver, Mirjam Wattenhofer:
Catching a viral video. J. Intell. Inf. Syst. 40(2): 241-259 (2013) - 2005
- [j1]Yacine Boufkhad, Olivier Dubois, Yannet Interian, Bart Selman:
Regular Random k-SAT: Properties of Balanced Formulas. J. Autom. Reason. 35(1-3): 181-200 (2005)
Conference and Workshop Papers
- 2023
- [c7]Yannet Interian, Sara Bernardini:
Learning Interpretable Heuristics for WalkSAT. KR 2023: 365-373 - 2010
- [c6]Tom Broxton, Yannet Interian, Jon Vaver, Mirjam Wattenhofer:
Catching a Viral Video. ICDM Workshops 2010: 296-304 - 2009
- [c5]Yannet Interian, Sundar Dorai-Raj, Igor Naverniouk, P. J. Opalinski, Kaustuv, Dan Zigmond:
Ad quality on TV: predicting television audience retention. KDD Workshop on Data Mining and Audience Intelligence for Advertising 2009: 85-91 - 2006
- [c4]Yannet Interian, Gabriel Corvera, Bart Selman, Ryan Williams:
Finding Small Unsatisfiable Cores to Prove Unsatisfiability of QBFs. AI&M 2006 - 2005
- [c3]Hubie Chen, Yannet Interian:
A Model for Generating Random Quantified Boolean Formulas. IJCAI 2005: 66-71 - 2004
- [c2]Yannet Interian:
Approximation Algorithm for Random MAX-kSAT. SAT 2004 - [c1]Yannet Interian:
Approximation Algorithm for Random MAX- kSAT. SAT (Selected Papers 2004: 173-182
Informal and Other Publications
- 2023
- [i6]Yannet Interian, Sara Bernardini:
Learning Interpretable Heuristics for WalkSAT. CoRR abs/2307.04608 (2023) - 2021
- [i5]Gilmer Valdes, Wilmer Arbelo, Yannet Interian, Jerome H. Friedman:
Lockout: Sparse Regularization of Neural Networks. CoRR abs/2107.07160 (2021) - 2019
- [i4]Efstathios D. Gennatas, Jerome H. Friedman, Lyle H. Ungar, Romain Pirracchio, Eric Eaton, L. Reichman, Yannet Interian, Charles B. Simone II, A. Auerbach, E. Delgado, Mark J. van der Laan, Timothy D. Solberg, Gilmer Valdes:
Expert-Augmented Machine Learning. CoRR abs/1903.09731 (2019) - [i3]Ibrahim Khoury, Danielle A. Savage, Addie Schnirel, Paul Intrevado, Yannet Interian:
ContamiNet: Detecting Contamination in Municipal Solid Waste. CoRR abs/1911.04583 (2019) - [i2]Gilmer Valdes, Yannet Interian, Efstathios D. Gennatas, Mark J. van der Laan:
Conditional Super Learner. CoRR abs/1912.06675 (2019) - [i1]Miguel Romero, Yannet Interian, Timothy D. Solberg, Gilmer Valdes:
Training Deep Learning models with small datasets. CoRR abs/1912.06761 (2019)
Coauthor Index
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