ASPS-L2.4
Optimizing Trading Strategies in Quantitative Markets using Multi-Agent Reinforcement Learning
Hengxi Zhang, Zhendong Shi, Yuanquan Hu, Wenbo Ding, Ercan Kuruoglu, Xiao-Ping Zhang, Tsinghua University, China
Session:
ASPS-L2: ASPS Systems Lecture Session Lecture
Track:
Applied Signal Processing Systems
Location:
Room E1
Presentation Time:
Tue, 16 Apr, 17:30 - 17:50 (UTC +9)
Session Chair:
Wenbo Ding, Tsinghua University
Session ASPS-L2
ASPS-L2.1: DICETRACK: LIGHTWEIGHT DICE CLASSIFICATION ON RESOURCE-CONSTRAINED PLATFORMS WITH OPTIMIZED DEEP LEARNING MODELS
Christophe EL Zeinaty, Univ. Rennes, INSA Rennes, CNRS, IETR - UMR 6164, France; Glenn Herrou, Wizama, France; Wassim Hamidouche, Daniel Menard, Univ. Rennes, INSA Rennes, CNRS, IETR - UMR 6164, France
ASPS-L2.2: ENHANCED DEEP REINFORCEMENT LEARNING FOR PARCEL SINGULATION IN NON-STATIONARY ENVIRONMENTS
Jiwei Shen, Hu Lu, Hao Zhang, Shujing Lyu, Yue Lu, East China Normal University, China
ASPS-L2.3: A LEARNING-BASED SYSTEM FOR AUTOMATIC INTENTIONAL NON-ADHERENCE DETECTION FROM DOSING VIDEOS
Shaolei Feng, Xiaoguang Lu, Deshana Kaushal Desai, Lei Guan, AiCure Inc., United States of America
ASPS-L2.4: Optimizing Trading Strategies in Quantitative Markets using Multi-Agent Reinforcement Learning
Hengxi Zhang, Zhendong Shi, Yuanquan Hu, Wenbo Ding, Ercan Kuruoglu, Xiao-Ping Zhang, Tsinghua University, China
ASPS-L2.5: DEEP LEARNING AMR MODEL INFERENCE ACCELERATION WITH CFU FOR EDGE SYSTEMS
Pavlo Hilei, Marian Petruk, Ukrainian Catholic University, Ukraine; Ievgen Korotkyi, Igor Sikorsky Kyiv Polytechnic Institute, Ukraine; Oleg Farenyuk, Ukrainian Catholic University, Ukraine
ASPS-L2.6: mmCount: Stationary Crowd Counting System Based on Commodity Millimeter-wave Radar
Kaiyuan Hu, Hongjie Liao, Mingxiao Li, Fangxin Wang, The Chinese University of Hong Kong, Shenzhen, China
Contacts