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Contributed Papers

Making Sense of Hidden Structures

Sun, Aug 2, 4:00 PM - 5:50 PM Room CC-254B Thomas M. Menino Convention & Exhibition Center

Kan ChenChair

Biometrics Section

6 Presentations

Deep generative conditional density regression in complex surveys: Application to oral health

4:05 PM - 4:20 PM

Dipankar Bandyopadhyay (Virginia Commonwealth University)

Co-authors: Snigdha Das (Texas A&M University), Debdeep Pati (University of Wisconsin-Madison)

Deep learning Generative adversarial networks Survey weighting Periodontal disease

One-hit logistic regression for multiple instance learning

4:20 PM - 4:35 PM

Eugene Demidenko (Geisel School of Medicine at Dartmouth)

binary classification bladder cancer Fisher scoring model-based classification p-value for classification

Clustering Sparse Multivariate Functional Data through Gaussian Mixture Models

4:35 PM - 4:50 PM

Andres Arguedas

Co-authors: Erjia Cui (University of Minnesota), Mark Fiecas (University of Minnesota)

Amyotrophic Lateral Sclerosis EM algorithm mixture model multivariate data sparse functional data

SADA: Safe and Adaptive Aggregation of Multiple Black-Box Predictions in Semi-Supervised Learning

4:50 PM - 5:05 PM

Jiawei Shan (University of Wisconsin-Madison)

Black-box models Prediction-powered inference Semiparametric efficiency Semi-supervised learning

Optimal Classification with Latent Clusters

5:05 PM - 5:20 PM

Co-authors: Chin-Tsang Chiang (National Taiwan University), Sheng-Hsin Fan (National Taiwan University), Alvin Lim (Emory University)

Asymptotic semiparametric efficiency Cluster-specific classifier Semiparametric elliptical model Optimal classification Receiver operating characteristic curve Semiparametric information criterion

Robust inference for risk heterogeneity with group imbalance

5:20 PM - 5:35 PM

Co-authors: Subha Maity (University of Michigan), Joel Dubin (University of Waterloo)

Underrepresented population Risk prediction Statistical learning Transfer learning Neyman orthogonalization

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