Online Inference of Topics with Latent Dirichlet Allocation. - Kevin Robert Canini; Lei Shi 009; Thomas L. Griffiths 001 (AISTATS, 2009)

Modeling Transfer Learning in Human Categorization with the Hierarchical Dirichlet Process. - Kevin Robert Canini; Mikhail M. Shashkov; Thomas L. Griffiths 001 (ICML, 2010)

A Nonparametric Bayesian Model of Multi-Level Category Learning. - Kevin Robert Canini; Thomas L. Griffiths 001 (AAAI, 2011)

Grow your own representations: Computational constructivism. - Joseph L. Austerweil; Thomas L. Griffiths 001; Todd M. Gureckis; Robert L. Goldstone; Kevin Robert Canini; Matt Jones 002 (CogSci, 2011)

Segmenting and Recognizing Human Action using Low-level Video Features. - Daphna Buchsbaum; Kevin Robert Canini; Thomas L. Griffiths 001 (CogSci, 2011)

Discovering Inductive Biases in Categorization through Iterated Learning. - Kevin Robert Canini; Thomas L. Griffiths 001; Wolf Vanpaemel; Michael L. Kalish (CogSci, 2011)

Finding Credible Information Sources in Social Networks Based on Content and Social Structure. - Kevin Robert Canini; Bongwon Suh; Peter Pirolli (SocialCom/PASSAT, 2011)

Nonparametric Hierarchical Bayesian Models of Categorization. - Kevin Robert Canini (2011)

Parallel Boosting with Momentum. - Indraneel Mukherjee; Kevin Robert Canini; Rafael M. Frongillo; Yoram Singer (ECML/PKDD (3), 2013)

Monotonic Calibrated Interpolated Look-Up Tables. - Maya R. Gupta; Andrew Cotter; Jan Pfeifer; Konstantin Voevodski; Kevin Robert Canini; Alexander Mangylov; Wojtek Moczydlowski (CoRR, 2015)

Launch and Iterate: Reducing Prediction Churn. - Mahdi Milani Fard; Quentin Cormier; Kevin Robert Canini; Maya R. Gupta (NIPS, 2016)

Fast and Flexible Monotonic Functions with Ensembles of Lattices. - Mahdi Milani Fard; Kevin Robert Canini; Andrew Cotter; Jan Pfeifer; Maya R. Gupta (NIPS, 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)

Deep Lattice Networks and Partial Monotonic Functions. - Seungil You; David Ding; Kevin Robert Canini; Jan Pfeifer; Maya R. Gupta (NIPS, 2017)

Diminishing Returns Shape Constraints for Interpretability and Regularization. - Maya R. Gupta; Dara Bahri; Andrew Cotter; Kevin Robert Canini (NeurIPS, 2018)

Regularization Strategies for Quantile Regression. - Taman Narayan; Serena Lutong Wang; Kevin Robert Canini; Maya R. Gupta (CoRR, 2021)

Fast Linear Interpolation. - Nathan Zhang; Kevin Robert Canini; Sean Silva; Maya R. Gupta (ACM J. Emerg. Technol. Comput. Syst., 2021)

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)