Hamed Valizadegan

According to our database, Hamed Valizadegan authored at least 23 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

TelescopeML - I. An End-to-End Python Package for Interpreting Telescope Datasets through Training Machine Learning Models, Generating Statistical Reports, and Visualizing Results.

Ehsan Gharib-Nezhad, Natasha E. Batalha, Hamed Valizadegan, Miguel J. S. Martinho, Mahdi Habibi, Gopal Nookula

CoRR, 2024

2023

Multiplicity Boost Of Transit Signal Classifiers: Validation of 69 New Exoplanets Using The Multiplicity Boost of ExoMiner.

Hamed Valizadegan, Miguel J. S. Martinho, Jon M. Jenkins, Douglas A. Caldwell, Joseph D. Twicken, Stephen T. Bryson

CoRR, 2023

2021

ExoMiner: A Highly Accurate and Explainable Deep Learning Classifier to Mine Exoplanets.

Hamed Valizadegan, Miguel J. S. Martinho, Laurent S. Wilkens, Jon M. Jenkins, Jeffrey Smith, Douglas A. Caldwell, Joseph D. Twicken, Pedro C. Gerum, Nikash Walia, Kaylie Hausknecht, Noa Y. Lubin, Stephen T. Bryson, Nikunj C. Oza

CoRR, 2021

2016

Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems.

Igor Melnyk, Bryan L. Matthews, Hamed Valizadegan, Arindam Banerjee, Nikunj C. Oza

J. Aerosp. Inf. Syst., 2016

2014

Learning classification models with soft-label information.

Quang Nguyen, Hamed Valizadegan, Milos Hauskrecht

J. Am. Medical Informatics Assoc., 2014

Relative Comparison Kernel Learning with Auxiliary Kernels.

Eric Heim, Hamed Valizadegan, Milos Hauskrecht

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2013

A temporal pattern mining approach for classifying electronic health record data.

Iyad Batal, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht

ACM Trans. Intell. Syst. Technol., 2013

Learning classification models from multiple experts.

Hamed Valizadegan, Quang Nguyen, Milos Hauskrecht

J. Biomed. Informatics, 2013

2012

Factorized Diffusion Map Approximation.

Saeed Amizadeh, Hamed Valizadegan, Milos Hauskrecht

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Sampling Strategies to Evaluate the Performance of Unknown Predictors.

Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrecht

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Learning Medical Diagnosis Models from Multiple Experts.

Hamed Valizadegan, Quang Nguyen, Milos Hauskrecht

Proceedings of the AMIA 2012, 2012

2011

Learning to trade off between exploration and exploitation in multiclass bandit prediction.

Hamed Valizadegan, Rong Jin, Shijun Wang

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Conditional Anomaly Detection with Soft Harmonic Functions.

Michal Valko, Branislav Kveton, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Learning Classification with Auxiliary Probabilistic Information.

Quang Nguyen, Hamed Valizadegan, Milos Hauskrecht

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

A Pattern Mining Approach for Classifying Multivariate Temporal Data.

Iyad Batal, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010

A Potential-based Framework for Online Multi-class Learning with Partial Feedback.

Shijun Wang, Rong Jin, Hamed Valizadegan

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

2009

Learning to Rank by Optimizing NDCG Measure.

Hamed Valizadegan, Rong Jin, Ruofei Zhang, Jianchang Mao

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008

Ranking refinement and its application to information retrieval.

Rong Jin, Hamed Valizadegan, Hang Li

Proceedings of the 17th International Conference on World Wide Web, 2008

Semi-Supervised Boosting for Multi-Class Classification.

Hamed Valizadegan, Rong Jin, Anil K. Jain

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

2007

Kernel Based Detection of Mislabeled Training Examples.

Hamed Valizadegan, Pang-Ning Tan

Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

A Probabilistic Substructure-Based Approach for Graph Classification.

H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jamal Fodeh, Pang-Ning Tan

Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), 2007

A Prototype-driven Framework for Change Detection in Data Stream Classification.

Hamed Valizadegan, Pang-Ning Tan

Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2007

2006

Generalized Maximum Margin Clustering and Unsupervised Kernel Learning.

Hamed Valizadegan, Rong Jin

Proceedings of the Advances in Neural Information Processing Systems 19, 2006