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cs.LG2026
Estimating Implicit Expected Log Density Ratios
Avi Amalanshu, Chandler Squires, Yizhou Lu +1
When exact probabilities cannot be computed, \emph{density ratio estimation (DRE)} is a key subroutine in the wide range of applications where density ratios appear, from experimen…
cs.LG2024
Entity Augmentation for Efficient Classification of Vertically Partitioned Data with Limited Overlap
Avi Amalanshu, Viswesh Nagaswamy, G. V. S. S. Prudhvi +2
Vertical Federated Learning (VFL) is a machine learning paradigm for learning from vertically partitioned data (i.e. features for each input are distributed across multiple "guest"…
cs.LG2024
Decoupled Vertical Federated Learning for Practical Training on Vertically Partitioned Data
Avi Amalanshu, Yash Sirvi, David I. Inouye
Vertical Federated Learning (VFL) is an emergent distributed machine learning paradigm for collaborative learning between clients who have disjoint features of common entities. How…