Yigong Hu
Columbia University
13 Papers
1 Citations
Yigong Hu is an academic researcher from Columbia University. The author has contributed to research in topics: Computer science & Chemistry. The author has an hindex of 1, co-authored 3 publications.
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Papers
High-performance solutions of geographically weighted regression in R
TL;DR: In this article , two high-performance R solutions for GWR via Multi-core Parallel (MP) and Compute Unified Device Architecture (CUDA) techniques, respectively GWR-MP and GWR -CUDA, were proposed.
Uncovering spatial heterogeneity in real estate prices via combined hierarchical linear model and geographically weighted regression
TL;DR: This study collected a second-hand real estate house price data set of Wuhan, in which each property is located the same as the community it belongs to and proposed an extension by combining the hierarchical linear model (HLM) and GWR, namely HLM-GWR to cope with these problems.
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Scheduling IDK classifiers with arbitrary dependences to minimize the expected time to successful classification
Tarek Abdelzaher,Kunal Agrawal,Sunita Baruah,Alan G. Burns,Robert F. Davis,Zhishan Guo,Yigong Hu +6 more
TL;DR: In this article , a generalized IDK classifier cascade is proposed to select the optimal sequence of classifiers required to minimize the expected (i.e. average) execution duration needed to achieve successful classification, subject to a constraint on quality, and optionally a latency constraint on the worst-case execution duration.
Demo Abstract: Wireless Glasses for Non-contact Facial Expression Monitoring
Yigong Hu,Jingping Nie,Yuanyuting Wang,Stephen Xia,Xiaofan Jiang +4 more
- 21 Apr 2020
TL;DR: This work presents a wireless glasses system for non-contact facial expression monitoring composed of an IR camera and an embedded processing unit mounted on a 3D-printed glasses frame, and a novel data processing pipeline running across the glasses platform and a computer.
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Underprovisioned GPUs: On Sufficient Capacity for Real-Time Mission-Critical Perception
Yigong Hu,Ila Gokarn,Shengzhong Liu,Archan Misra,Tarek Abdelzaher +4 more
- 01 Jul 2023
TL;DR: This paper derives an attention allocation policy, called canvas-based attention scheduling, that decides which parts of each frame of each device to inspect, and a corresponding schedulability condition that relates the spatiotemporal properties of surrounding objects to the ability of the edge-based perception subsystem to keep up with the state of the environment in real-time.
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