Search Results for author:
Found 7 papers, 2 papers with code
L3Cube-MahaSocialNER: A Social Media based Marathi NER Dataset and BERT models
This work introduces the L3Cube-MahaSocialNER dataset, the first and largest social media dataset specifically designed for Named Entity Recognition (NER) in the Marathi language.
On Significance of Subword tokenization for Low Resource and Efficient Named Entity Recognition: A case study in Marathi
In this work, we focus on NER for low-resource language and present our case study in the context of the Indian language Marathi.
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning
The integration of machine learning (ML) in numerous critical applications introduces a range of privacy concerns for individuals who provide their datasets for model training.
SNAP: Efficient Extraction of Private Properties with Poisoning
Property inference attacks allow an adversary to extract global properties of the training dataset from a machine learning model.
SafeNet: The Unreasonable Effectiveness of Ensembles in Private Collaborative Learning
Secure multiparty computation (MPC) has been proposed to allow multiple mutually distrustful data owners to jointly train machine learning (ML) models on their combined data.
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning
Machine learning has started to be deployed in fields such as healthcare and finance, which propelled the need for and growth of privacy-preserving machine learning (PPML).
ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction
In this work, we present concretely-efficient protocols for secure $3$-party computation (3PC) over a ring of integers modulo $2^{\ell}$ tolerating one corruption, both with semi-honest and malicious security.
