papers

Publications (5)

cs.RO2026

Flow-Enabled Generalization to Human Demonstrations in Few-Shot Imitation Learning

Runze Tang, Penny Sweetser

Imitation Learning (IL) enables robots to learn complex skills from demonstrations without explicit task modeling, but it typically requires large amounts of demonstrations, creati…

stat.ME2016

Empirical Bayes Estimation for the Stochastic Blockmodel

Shakira Suwan, Dominic S. Lee, Runze Tang +3

Inference for the stochastic blockmodel is currently of burgeoning interest in the statistical community, as well as in various application domains as diverse as social networks, c…

stat.ML2015

A model selection approach for clustering a multinomial sequence with non-negative factorization

Nam H. Lee, Runze Tang, Carey E. Priebe +1

We consider a problem of clustering a sequence of multinomial observations by way of a model selection criterion. We propose a form of a penalty term for the model selection proced…

stat.ME2017

Robust Estimation from Multiple Graphs under Gross Error Contamination

Runze Tang, Minh Tang, Joshua T. Vogelstein +1

Estimation of graph parameters based on a collection of graphs is essential for a wide range of graph inference tasks. In practice, weighted graphs are generally observed with edge…

stat.ME2018

Connectome Smoothing via Low-rank Approximations

Runze Tang, Michael Ketcha, Alexandra Badea +5

In statistical connectomics, the quantitative study of brain networks, estimating the mean of a population of graphs based on a sample is a core problem. Often, this problem is esp…