30 citations · 32 across the 5 of their papers we have counts for
5 papers
Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
Mathav Raj J, Kushala VM, Harikrishna Warrier +1
There is a compelling necessity from enterprises for fine tuning LLMs (Large Language Models) o get them trained on proprietary domain knowledge. The challenge is to imbibe the LLM…
Benchmarking with MIMIC-IV, an irregular, spare clinical time series dataset
Hung Bui, Harikrishna Warrier, Yogesh Gupta
Electronic health record (EHR) is more and more popular, and it comes with applying machine learning solutions to resolve various problems in the domain. This growing research area…
Federated Learning for Non-IID Data via Client Variance Reduction and Adaptive Server Update
Hiep Nguyen, Lam Phan, Harikrishna Warrier +1
Federated learning (FL) is an emerging technique used to collaboratively train a global machine learning model while keeping the data localized on the user devices. The main obstac…
Survival Analysis on Structured Data using Deep Reinforcement Learning
Renith G, Harikrishna Warrier, Yogesh Gupta
Survival analysis is playing a major role in manufacturing sector by analyzing occurrence of any unwanted event based on the input data. Predictive maintenance, which is a part of…
Network state Estimation using Raw Video Analysis: vQoS-GAN based non-intrusive Deep Learning Approach
Renith G, Harikrishna Warrier, Yogesh Gupta
Content based providers transmits real time complex signal such as video data from one region to another. During this transmission process, the signals usually end up distorted or…