33 citations · 93 across the 16 of their papers we have counts for
6 papers · 1 filter
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections
Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy +1
Two-dimensional embeddings remain the dominant approach to visualize high dimensional data. The choice of embeddings ranges from highly non-linear ones, which can capture complex r…
Distribution-Preserving k-Anonymity
Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Preserving the privacy of individuals by protecting their sensitive attributes is an important consideration during microdata release. However, it is equally important to preserve…
An End-To-End Machine Learning Pipeline That Ensures Fairness Policies
Samiulla Shaikh, Harit Vishwakarma, Sameep Mehta +3
In consequential real-world applications, machine learning (ML) based systems are expected to provide fair and non-discriminatory decisions on candidates from groups defined by pro…
Multitask Learning using Task Clustering with Applications to Predictive Modeling and GWAS of Plant Varieties
Ming Yu, Addie M. Thompson, Karthikeyan Natesan Ramamurthy +2
Inferring predictive maps between multiple input and multiple output variables or tasks has innumerable applications in data science. Multi-task learning attempts to learn the maps…
Distributed Bundle Adjustment
Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Aravkin +2
Most methods for Bundle Adjustment (BA) in computer vision are either centralized or operate incrementally. This leads to poor scaling and affects the quality of solution as the nu…
Learning Robust Representations for Computer Vision
Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy +1
Unsupervised learning techniques in computer vision often require learning latent representations, such as low-dimensional linear and non-linear subspaces. Noise and outliers in th…