30 citations · 35 across the 3 of their papers we have counts for
5 papers
Efficient Encrypted Inference on Ensembles of Decision Trees
Kanthi Sarpatwar, Karthik Nandakumar, Nalini Ratha +4
Data privacy concerns often prevent the use of cloud-based machine learning services for sensitive personal data. While homomorphic encryption (HE) offers a potential solution by e…
Efficient CNN Building Blocks for Encrypted Data
Nayna Jain, Karthik Nandakumar, Nalini Ratha +2
Machine learning on encrypted data can address the concerns related to privacy and legality of sharing sensitive data with untrustworthy service providers. Fully Homomorphic Encryp…
Learning and Recognizing Archeological Features from LiDAR Data
Conrad M Albrecht, Chris Fisher, Marcus Freitag +4
We present a remote sensing pipeline that processes LiDAR (Light Detection And Ranging) data through machine & deep learning for the application of archeological feature detection…
RepMet: Representative-based metric learning for classification and one-shot object detection
Leonid Karlinsky, Joseph Shtok, Sivan Harary +5
Distance metric learning (DML) has been successfully applied to object classification, both in the standard regime of rich training data and in the few-shot scenario, where each ca…
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…