no code implementations • 8 May 2024 • Varun Nagaraj Rao, Eesha Agarwal, Samantha Dalal, Dan Calacci, Andrés Monroy-Hernández
This study introduces QuaLLM, a novel LLM-based framework to analyze and extract quantitative insights from text data on online forums.
no code implementations • 16 Feb 2019 • Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Anirudh Goyal, Peter Krafft, Esteban Moro, Alex Pentland
A common technique to improve learning performance in deep reinforcement learning (DRL) and many other machine learning algorithms is to run multiple learning agents in parallel.
no code implementations • 30 Nov 2018 • Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Peter Krafft, Esteban Moro, Alex `Sandy' Pentland
This is an important problem because a common technique to improve speed and robustness of learning in deep reinforcement learning and many other machine learning algorithms is to run multiple learning agents in parallel.
no code implementations • 30 Nov 2017 • Dhaval Adjodah, Dan Calacci, Yan Leng, Peter Krafft, Esteban Moro, Alex Pentland
We draw upon a previously largely untapped literature on human collective intelligence as a source of inspiration for improving deep learning.