Kevin Robert Canini

According to our database, Kevin Robert Canini authored at least 18 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Expected Pinball Loss For Quantile Regression And Inverse CDF Estimation.

Taman Narayan, Serena Lutong Wang, Kevin Robert Canini, Maya R. Gupta

Trans. Mach. Learn. Res., 2024

2021

Fast Linear Interpolation.

Nathan Zhang, Kevin Robert Canini, Sean Silva, Maya R. Gupta

ACM J. Emerg. Technol. Comput. Syst., 2021

Regularization Strategies for Quantile Regression.

Taman Narayan, Serena Lutong Wang, Kevin Robert Canini, Maya R. Gupta

CoRR, 2021

2018

Diminishing Returns Shape Constraints for Interpretability and Regularization.

Maya R. Gupta, Dara Bahri, Andrew Cotter, Kevin Robert Canini

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Deep Lattice Networks and Partial Monotonic Functions.

Seungil You, David Ding, Kevin Robert Canini, Jan Pfeifer, Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Monotonic Calibrated Interpolated Look-Up Tables.

Maya R. Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Robert Canini, Alexander Mangylov, Wojtek Moczydlowski, Alexander Van Esbroeck

J. Mach. Learn. Res., 2016

Fast and Flexible Monotonic Functions with Ensembles of Lattices.

Mahdi Milani Fard, Kevin Robert Canini, Andrew Cotter, Jan Pfeifer, Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Launch and Iterate: Reducing Prediction Churn.

Mahdi Milani Fard, Quentin Cormier, Kevin Robert Canini, Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Monotonic Calibrated Interpolated Look-Up Tables.

Maya R. Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Robert Canini, Alexander Mangylov, Wojtek Moczydlowski

CoRR, 2015

2013

Parallel Boosting with Momentum.

Indraneel Mukherjee, Kevin Robert Canini, Rafael M. Frongillo, Yoram Singer

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

2011

Nonparametric Hierarchical Bayesian Models of Categorization.

Kevin Robert Canini

PhD thesis, 2011

Finding Credible Information Sources in Social Networks Based on Content and Social Structure.

Kevin Robert Canini, Bongwon Suh, Peter Pirolli

Proceedings of the PASSAT/SocialCom 2011, Privacy, 2011

Discovering Inductive Biases in Categorization through Iterated Learning.

Kevin Robert Canini, Thomas L. Griffiths, Wolf Vanpaemel, Michael L. Kalish

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

Segmenting and Recognizing Human Action using Low-level Video Features.

Daphna Buchsbaum, Kevin Robert Canini, Thomas L. Griffiths

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

Grow your own representations: Computational constructivism.

Joseph L. Austerweil, Thomas L. Griffiths, Todd M. Gureckis, Robert L. Goldstone, Kevin Robert Canini, Matt Jones

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

A Nonparametric Bayesian Model of Multi-Level Category Learning.

Kevin Robert Canini, Thomas L. Griffiths

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Modeling Transfer Learning in Human Categorization with the Hierarchical Dirichlet Process.

Kevin Robert Canini, Mikhail M. Shashkov, Thomas L. Griffiths

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

Online Inference of Topics with Latent Dirichlet Allocation.

Kevin Robert Canini, Lei Shi, Thomas L. Griffiths

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009