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Michael J. Higgins

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • stat.ME2
  • cs.SI1
  • stat.ML1

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

stat.ME2020

The Benefits of Probability-Proportional-to-Size Sampling in Cluster-Randomized Experiments

Yeng Xiong, Michael J. Higgins

In a cluster-randomized experiment, treatment is assigned to clusters of individual units of interest--households, classrooms, villages, etc.--instead of the units themselves. The…

cs.SI2019

A new method for quantifying network cyclic structure to improve community detection

Behnaz Moradi-Jamei, Heman Shakeri, Pietro Poggi-Corradini +1

A distinguishing property of communities in networks is that cycles are more prevalent within communities than across communities. Thus, the detection of these communities may be a…

stat.ML2019

Hybridized Threshold Clustering for Massive Data

Jianmei Luo, ChandraVyas Annakula, Aruna Sai Kannamareddy +3

As the size n of datasets become massive, many commonly-used clustering algorithms (for example, k-means or hierarchical agglomerative clustering (HAC) require prohibitive comp…

stat.ME2019

From one environment to many: The problem of replicability of statistical inferences

James J. Higgins, Michael J. Higgins, Jinguang Lin

Among plausible causes for replicability failure, one that has not received sufficient attention is the environment in which the research is conducted. Consisting of the population…

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