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cs.LG2025
t-SNE Exaggerates Clusters, Provably
Noah Bergam, Szymon Snoeck, Nakul Verma
Central to the widespread use of t-distributed stochastic neighbor embedding (t-SNE) is the conviction that it produces visualizations whose structure roughly matches that of the i…
cs.CG2025
Compressibility Barriers to Neighborhood-Preserving Data Visualizations
Szymon Snoeck, Noah Bergam, Nakul Verma
To what extent is it possible to visualize high-dimensional data in two- or three-dimensional plots? We reframe this question in terms of embedding -vertex graphs (representing…
cs.LG2025
ClusterSC: Advancing Synthetic Control with Donor Selection
Saeyoung Rho, Andrew Tang, Noah Bergam +2
In causal inference with observational studies, synthetic control (SC) has emerged as a prominent tool. SC has traditionally been applied to aggregate-level datasets, but more rece…