Nvidia shrinks LLM memory 20x without changing model weights

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.
IEEE

A Review of Machine Learning and Deep Learning Trends in EEG-Based Epileptic Seizure Prediction

Abstract: Epileptic seizures impair patients’ health and quality of life, and electroencephalography (EEG)-based prediction enables timely intervention. Early work on epileptic seizure prediction ...
IEEE

Adaptive Quantization and Differential Privacy Federated Learning Framework

Abstract: Federated Learning (FL) enables devices to collaboratively train machine learning models without sharing raw data, promoting privacy-preserving AI. However, practical deployment faces ...