
Scalable BottomUp Hierarchical Clustering
Bottomup algorithms such as the classic hierarchical agglomerative clus...
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Big Bird: Transformers for Longer Sequences
Transformersbased models, such as BERT, have been one of the most succe...
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Distributed, partially collapsed MCMC for Bayesian Nonparametrics
Bayesian nonparametric (BNP) models provide elegant methods for discover...
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Transformation Autoregressive Networks
The fundamental task of general density estimation has been of keen inte...
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Personalized Survival Prediction with Contextual Explanation Networks
Accurate and transparent prediction of cancer survival times on the leve...
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The Intriguing Properties of Model Explanations
Linear approximations to the decision boundary of a complex model have b...
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Contextual Explanation Networks
We introduce contextual explanation networks (CENs)a class of models ...
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Parallel Markov Chain Monte Carlo for the Indian Buffet Process
Indian Buffet Process based models are an elegant way for discovering un...
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Science Question Answering using Instructional Materials
We provide a solution for elementary science test using instructional ma...
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Bayesian Nonparametric KernelLearning
Kernel methods are ubiquitous tools in machine learning. They have prove...
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Exact and Efficient Parallel Inference for Nonparametric Mixture Models
Nonparametric mixture models based on the Dirichlet process are an elega...
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A nonparametric mixture model for topic modeling over time
A single, stationary topic model such as latent Dirichlet allocation is ...
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Avinava Dubey
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