no code implementations • 12 Mar 2024 • Masoud Shokrnezhad, Hao Yu, Tarik Taleb, Richard Li, Kyunghan Lee, Jaeseung Song, Cedric Westphal
Hence, this paper presents the concept of Adaptable CNC (ACNC) as an autonomous Machine Learning (ML)-aided mechanism crafted for the joint orchestration of computing and network resources, catering to dynamic and voluminous user requests with stringent requirements.
no code implementations • 16 Oct 2023 • Paul Ruvolo, Ayush Chakraborty, Rucha Dave, Richard Li, Duncan Mazza, Xierui Shen, Raiyan Siddique, Krishna Suresh
We present a system for creating building-scale, easily navigable 3D maps using mainstream smartphones.
no code implementations • IEEE MetaCom, Kyoto 2023 • Hamidreza Mazandarani, Masoud Shokrnezhad, Tarik Taleb, Richard Li
The Metaverse is a new paradigm that aims to create a virtual environment consisting of numerous worlds, each of which will offer a different set of services.
no code implementations • 7 Jul 2023 • Zachary Englhardt, Richard Li, Dilini Nissanka, Zhihan Zhang, Girish Narayanswamy, Joseph Breda, Xin Liu, Shwetak Patel, Vikram Iyer
We leverage this finding to study how human programmers interact with these tools, and develop an human-AI based software engineering workflow for building embedded systems.
no code implementations • 18 Aug 2022 • Richard Li, Carlos Esteves, Ameesh Makadia, Pulkit Agrawal
We present a system for accurately predicting stable orientations for diverse rigid objects.
1 code implementation • 30 Jun 2022 • Andy Zou, Tristan Xiao, Ryan Jia, Joe Kwon, Mantas Mazeika, Richard Li, Dawn Song, Jacob Steinhardt, Owain Evans, Dan Hendrycks
We test language models on our forecasting task and find that performance is far below a human expert baseline.
1 code implementation • 23 Dec 2019 • Richard Li, Allan Jabri, Trevor Darrell, Pulkit Agrawal
Learning robotic manipulation tasks using reinforcement learning with sparse rewards is currently impractical due to the outrageous data requirements.