5 citations · 16 across the 7 of their papers we have counts for
7 papers
On Regularization and Inference with Label Constraints
Kaifu Wang, Hangfeng He, Tin D. Nguyen +2
Prior knowledge and symbolic rules in machine learning are often expressed in the form of label constraints, especially in structured prediction problems. In this work, we compare…
Are you using test log-likelihood correctly?
Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen +1
Test log-likelihood is commonly used to compare different models of the same data or different approximate inference algorithms for fitting the same probabilistic model. We present…
Many processors, little time: MCMC for partitions via optimal transport couplings
Tin D. Nguyen, Brian L. Trippe, Tamara Broderick
Markov chain Monte Carlo (MCMC) methods are often used in clustering since they guarantee asymptotically exact expectations in the infinite-time limit. In finite time, though, slow…
Measuring the robustness of Gaussian processes to kernel choice
William T. Stephenson, Soumya Ghosh, Tin D. Nguyen +3
Gaussian processes (GPs) are used to make medical and scientific decisions, including in cardiac care and monitoring of atmospheric carbon dioxide levels. Notably, the choice of GP…
Optimal transport couplings of Gibbs samplers on partitions for unbiased estimation
Brian L. Trippe, Tin D. Nguyen, Tamara Broderick
Computational couplings of Markov chains provide a practical route to unbiased Monte Carlo estimation that can utilize parallel computation. However, these approaches depend crucia…
Independent finite approximations for Bayesian nonparametric inference
Tin D. Nguyen, Jonathan Huggins, Lorenzo Masoero +2
Completely random measures (CRMs) and their normalizations (NCRMs) offer flexible models in Bayesian nonparametrics. But their infinite dimensionality presents challenges for infer…
Approximate Cross-Validation for Structured Models
Soumya Ghosh, William T. Stephenson, Tin D. Nguyen +2
Many modern data analyses benefit from explicitly modeling dependence structure in data -- such as measurements across time or space, ordered words in a sentence, or genes in a gen…