4 papers
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…
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"…
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…
[Re] CLRNet: Cross Layer Refinement Network for Lane Detection
Viswesh N, Kaushal Jadhav, Avi Amalanshu +5
The following work is a reproducibility report for CLRNet: Cross Layer Refinement Network for Lane Detection. The basic code was made available by the author. The paper proposes a…