Person:
Huo, Xiaoming

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https://hdl.handle.net/1853/71354
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    ML@GT Lab presents LAB LIGHTNING TALKS 2020
    ( 2020-12-04) AlRegib, Ghassan ; Chau, Duen Horng ; Chava, Sudheer ; Cohen, Morris B. ; Davenport, Mark A. ; Desai, Deven ; Dovrolis, Constantine ; Essa, Irfan ; Gupta, Swati ; Huo, Xiaoming ; Kira, Zsolt ; Li, Jing ; Maguluri, Siva Theja ; Pananjady, Ashwin ; Prakash, B. Aditya ; Riedl, Mark O. ; Romberg, Justin ; Xie, Yao ; Zhang, Xiuwei
    Labs affiliated with the Machine Learning Center at Georgia Tech (ML@GT) will have the opportunity to share their research interests, work, and unique aspects of their lab in three minutes or less to interested graduate students, Georgia Tech faculty, and members of the public. Participating labs include: Yao’s Group - Yao Xie, H. Milton Stewart School of Industrial Systems and Engineering (ISyE); Huo Lab - Xiaoming Huo, ISyE; LF Radio Lab – Morris Cohen, School of Electrical Computing and Engineering (ECE); Polo Club of Data Science – Polo Chau, CSE; Network Science – Constantine Dovrolis, School of Computer Science; CLAWS – Srijan Kumar, CSE; Control, Optimization, Algorithms, and Randomness (COAR) Lab – Siva Theja Maguluri, ISyE; Entertainment Intelligence Lab and Human Centered AI Lab – Mark Riedl, IC; Social and Language Technologies (SALT) Lab – Diyi Yang, IC; FATHOM Research Group – Swati Gupta, ISyE; Zhang's CompBio Lab – Xiuwei Zhang, CSE; Statistical Machine Learning - Ashwin Pananjady, ISyE and ECE; AdityaLab - B. Aditya Prakash, CSE; OLIVES - Ghassan AlRegib, ECE; Robotics Perception and Learning (RIPL) – Zsolt Kira, IC; Eye-Team - Irfan Essa, IC; and Mark Davenport, ECE.
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    Beamlet-like Data Processing for Accelerated Path-Planning Using Multiscale Information of the Environment
    (Georgia Institute of Technology, 2010-12) Lu, Yibiao ; Huo, Xiaoming ; Tsiotras, Panagiotis
    We consider the deterministic path-planning problem dealing with the single-pair shortest path on a given graph. We propose a multiscale version of the well known A* algorithm (m-A*), which utilizes information of the environment at distinct scales. This information is collected via a bottom-up fusion method. Comparing with existing algorithms such as Dijkstra’s or A*, the use of multiscale information leads to an improvement in terms of computational complexity.
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    Fundamentals and applications of connect the dots methods
    (Georgia Institute of Technology, 2010-08-01) Huo, Xiaoming ; Tovey, Craig A.