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On regularization and inference with label constraints
Prior knowledge and symbolic rules in machine learning are often expressed in the form of label constraints, especially in structured …
Kaifu Wang, Hangfeng He, Tin Nguyen, Piyush Kumar, Dan Roth
Many processors, little time: MCMC for partitions via optimal transport couplings
Markov chain Monte Carlo (MCMC) methods are often used in clustering since they guarantee asymptotically exact expectations in the …
Tin Nguyen, Brian L. Trippe, Tamara Broderick
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Measuring the robustness of Gaussian processes to kernel choice
Gaussian processes (GPs) are used to make medical and scientific decisions, including in cardiac care and monitoring of atmospheric …
William T. Stephenson, Soumya Ghosh, Tin Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick
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Approximate cross-validation for structured models
Many modern data analyses benefit from explicitly modeling dependence structure in data – such as measurements across time or …
William T. Stephenson, Soumya Ghosh, Tin Nguyen, Sameer K. Deshpande, Tamara Broderick
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PAC-Bayes Tree: weighted subtrees with guarantees
We present a weighted-majority classification approach over subtrees of a fixed tree, which provably achieves excess-risk of the same …
Tin Nguyen, Samory Kpotufe
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