#Machine Learning
10 items
Posts
The AI Copyright Challenge: Building Legal Frameworks for Generative AI
As generative AI transforms content creation, we need new frameworks that respect copyright while enabling innovation. Here's how we can build them.
Why Deepfake Detection Needs Decentralization
As deepfake technology becomes more sophisticated, centralized detection approaches are failing. Here's why we need decentralized solutions.
Tackling Data Imbalance in Federated Learning
How Fed-Focal Loss addresses one of the most challenging problems in distributed machine learning: handling imbalanced data across federated clients.
Publications
arXiv
Curriculum generation using Autoencoder based continuous optimization
Dipankar Sarkar , M Gupta
arXiv
One Shot Audio to Animated Video Generation
N Kumar , S Goel , A Narang , B Lall , M Hasan , P Agarwal , Dipankar Sarkar
Projects
Deepfake Detection Network
Decentralized Deepfake Detection Blockchain Network using Dynamic Algorithm Management
Fragaria
Advanced Chain of Thought (CoT) Reasoning API with Reinforcement Learning (RL)
Viz: QLoRA-based Copyright Marketplace
A QLoRA-based Marketplace Framework for Legally Compliant Generative AI
Talks & Events
Fed-Focal Loss for Imbalanced Data Classification in Federated Learning
International Workshop on Federated Learning for User Privacy and Data Confidentiality (FL-IJCAI'20)
A presentation on applying Focal Loss to Federated Learning for handling imbalanced data classification
Decentralized AI: Privacy, Fairness, and the Future of Machine Learning
AI & Web3 Summit 2024
A keynote on the convergence of federated learning, blockchain, and decentralized systems for privacy-preserving AI