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math.ST2025
Confidence Sets for Multidimensional Scaling
Siddharth Vishwanath, Ery Arias-Castro
We develop a formal statistical framework for classical multidimensional scaling (CMDS) applied to noisy dissimilarity data. We establish distributional convergence results for the…
cs.LG2025
Signal Recovery from Random Dot-Product Graphs Under Local Differential Privacy
Siddharth Vishwanath, Jonathan Hehir
We consider the problem of recovering latent information from graphs under -edge local differential privacy where the presence of relationships/edges between two users…
math.ST2025
Minimax Optimality of Classical Scaling Under General Noise Conditions
Siddharth Vishwanath, Ery Arias-Castro
We establish the consistency of classical scaling under a broad class of noise models, encompassing many commonly studied cases in literature. Our approach requires only finite fou…