research
∙
09/21/2023
The Cambridge Law Corpus: A Corpus for Legal AI Research
We introduce the Cambridge Law Corpus (CLC), a corpus for legal AI resea...
share
research
∙
03/25/2022
Probabilistic Embeddings with Laplacian Graph Priors
We introduce probabilistic embeddings using Laplacian priors (PELP). The...
research
∙
01/25/2021
Rapid mixing in unimodal landscapes and efficient simulatedannealing for multimodal distributions
We consider nearest neighbor weighted random walks on the d-dimensional ...
research
∙
09/01/2020
Robust, Accurate Stochastic Optimization for Variational Inference
We consider the problem of fitting variational posterior approximations ...
research
∙
08/25/2020
Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance
When evaluating and comparing models using leave-one-out cross-validatio...
research
∙
08/24/2020
Uncertainty in Bayesian Leave-One-Out Cross-Validation Based Model Comparison
Leave-one-out cross-validation (LOO-CV) is a popular method for comparin...
research
∙
03/09/2020
When are Bayesian model probabilities overconfident?
Bayesian model comparison is often based on the posterior distribution o...
research
∙
01/03/2020
Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data
Recently, new methods for model assessment, based on subsampling and pos...
research
∙
09/03/2019
Interpretable Word Embeddings via Informative Priors
Word embeddings have demonstrated strong performance on NLP tasks. Howev...
research
∙
06/06/2019
Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models
Nonparametric extensions of topic models such as Latent Dirichlet Alloca...
research
∙
04/24/2019
Bayesian leave-one-out cross-validation for large data
Model inference, such as model comparison, model checking, and model sel...
research
∙
05/18/2018
Multivariate Analysis of Orthogonal Range Searching and Graph Distances Parameterized by Treewidth
We show that the eccentricities, diameter, radius, and Wiener index of a...
research
∙
04/12/2017
Polya Urn Latent Dirichlet Allocation: a doubly sparse massively parallel sampler
Latent Dirichlet Allocation (LDA) is a topic model widely used in natura...
research
∙
01/31/2016
DOLDA - a regularized supervised topic model for high-dimensional multi-class regression
Generating user interpretable multi-class predictions in data rich envir...
research
∙
06/11/2015