Caruana, Rich

44 publications

NeurIPSW 2024 GAMformer: Exploring In-Context Learning for Generalized Additive Models Andreas C Mueller, Julien Siems, Harsha Nori, Rich Caruana, Frank Hutter

NeurIPSW 2024 GAMformer: Exploring In-Context Learning for Generalized Additive Models Andreas C Mueller, Julien Siems, Harsha Nori, David Salinas, Arber Zela, Rich Caruana, Frank Hutter

MLJ 2023 Considerations When Learning Additive Explanations for Black-Box Models Sarah Tan, Giles Hooker, Paul Koch, Albert Gordo, Rich Caruana

NeurIPSW 2023 Elephants Never Forget: Testing Language Models for Memorization of Tabular Data Sebastian Bordt, Harsha Nori, Rich Caruana

NeurIPSW 2023 Explaining High-Dimensional Text Classifiers Odelia Melamed, Rich Caruana

AISTATS 2022 Dropout as a Regularizer of Interaction Effects Benjamin J. Lengerich, Eric Xing, Rich Caruana

CLeaR 2022 Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan

ICLR 2022 NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning Chun-Hao Chang, Rich Caruana, Anna Goldenberg

ICML 2021 Accuracy, Interpretability, and Differential Privacy via Explainable Boosting Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni

NeurIPS 2021 Neural Additive Models: Interpretable Machine Learning with Neural Nets Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Ben Lengerich, Rich Caruana, Geoffrey E. Hinton

AISTATS 2020 Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana

NeurIPS 2019 Efficient Forward Architecture Search Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric J Horvitz, Debadeepta Dey

ICLR 2017 Do Deep Convolutional Nets Really Need to Be Deep and Convolutional? Gregor Urban, Krzysztof J. Geras, Samira Ebrahimi Kahou, Özlem Aslan, Shengjie Wang, Abdelrahman Mohamed, Matthai Philipose, Matthew Richardson, Rich Caruana

AAAI 2017 Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz

ICML 2016 Analysis of Deep Neural Networks with Extended Data Jacobian Matrix Shengjie Wang, Abdel-rahman Mohamed, Rich Caruana, Jeff Bilmes, Matthai Plilipose, Matthew Richardson, Krzysztof Geras, Gregor Urban, Ozlem Aslan

CVPR 2016 Detecting Migrating Birds at Night Jia-Bin Huang, Rich Caruana, Andrew Farnsworth, Steve Kelling, Narendra Ahuja

AAAI 2014 Active Learning with Model Selection Alnur Ali, Rich Caruana, Ashish Kapoor

NeurIPS 2014 Do Deep Nets Really Need to Be Deep? Jimmy Ba, Rich Caruana

NeurIPS 2013 Using Multiple Samples to Learn Mixture Models Jason Lee, Ran Gilad-Bachrach, Rich Caruana

ECML-PKDD 2009 On Feature Selection, Bias-Variance, and Bagging M. Arthur Munson, Rich Caruana

ICML 2008 An Empirical Evaluation of Supervised Learning in High Dimensions Rich Caruana, Nikolaos Karampatziakis, Ainur Yessenalina

ICML 2008 Detecting Statistical Interactions with Additive Groves of Trees Daria Sorokina, Rich Caruana, Mirek Riedewald, Daniel Fink

ECML-PKDD 2008 Improving Classification with Pairwise Constraints: A Margin-Based Approach Nam Nguyen, Rich Caruana

AISTATS 2007 Inductive Transfer for Bayesian Network Structure Learning Alexandru Niculescu-Mizil, Rich Caruana

ICML 2006 An Empirical Comparison of Supervised Learning Algorithms Rich Caruana, Alexandru Niculescu-Mizil

UAI 2005 Obtaining Calibrated Probabilities from Boosting Alexandru Niculescu-Mizil, Rich Caruana

ICML 2005 Predicting Good Probabilities with Supervised Learning Alexandru Niculescu-Mizil, Rich Caruana

ICML 2004 Ensemble Selection from Libraries of Models Rich Caruana, Alexandru Niculescu-Mizil, Geoff Crew, Alex Ksikes

NeurIPS 2001 (Not) Bounding the True Error John Langford, Rich Caruana

AISTATS 2001 A Non-Parametric EM-Style Algorithm for Imputing Missing Values Rich Caruana

ICML 2000 FeatureBoost: A Meta-Learning Algorithm That Improves Model Robustness Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum

NeurIPS 2000 Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping Rich Caruana, Steve Lawrence, C. Lee Giles

MLJ 1997 Multitask Learning Rich Caruana

ICML 1996 Algorithms and Applications for Multitask Learning Rich Caruana

NeurIPS 1996 Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs Rich Caruana, Virginia R. de Sa

ICML 1995 Removing the Genetics from the Standard Genetic Algorithm Shumeet Baluja, Rich Caruana

NeurIPS 1995 Using the Future to "Sort Out" the Present: Rankprop and Multitask Learning for Medical Risk Evaluation Rich Caruana, Shumeet Baluja, Tom Mitchell

ICML 1994 Greedy Attribute Selection Rich Caruana, Dayne Freitag

NeurIPS 1994 Learning Many Related Tasks at the Same Time with Backpropagation Rich Caruana

ICML 1993 Multitask Learning: A Knowledge-Based Source of Inductive Bias Rich Caruana

IJCAI 1989 Representation and Hidden Bias II: Eliminating Defining Length Bias in Genetic Search via Shuffle Crossover Rich Caruana, Larry J. Eshelman, J. David Schaffer

ICML 1989 Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms Rich Caruana, J. David Schaffer, Larry J. Eshelman

ICML 1988 Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms Rich Caruana, J. David Schaffer

UAI 1987 The Automatic Training of Rule Bases That Use Numerical Uncertainty Representations Rich Caruana