937 citations
- Commonwealth Scientific and Industrial Research OrganisationAU42 papers
- Australian National UniversityAU12 papers
- Data61AU11 papers
- The University of MelbourneAU8 papers
- Beijing University of Posts and TelecommunicationsCN5 papers
- Monash UniversityAU5 papers
- The University of SydneyAU5 papers
- Carnegie Mellon UniversityUS4 papers
- University of Technology SydneyAU4 papers
- Curtin UniversityAU3 papers
- International Centre for Radio Astronomy ResearchAU3 papers
- Queensland University of TechnologyAU3 papers
7 papers · 1 filter
Cooperative Heterogeneous Deep Reinforcement Learning
Han Zheng, Pengfei Wei, Jing Jiang +3
Numerous deep reinforcement learning agents have been proposed, and each of them has its strengths and flaws. In this work, we present a Cooperative Heterogeneous Deep Reinforcemen…
ServiceNet: A P2P Service Network
Ji Liu, Hang Zhao, Jiyuan Yang +4
Given a large number of online services on the Internet, from time to time, people are still struggling to find out the services that they need. On the other hand, when there are c…
Deep neural network for optimal retirement consumption in defined contribution pension system
Wen Chen, Nicolas Langrené
In this paper, we develop a deep neural network approach to solve a lifetime expected mortality-weighted utility-based model for optimal consumption in the decumulation phase of a…
Analysis and Optimization of Service Delay for Multi-quality Videos in Multi-tier Heterogeneous Network with Random Caching
Xuewei Zhang, Tiejun Lv, Yuan Ren +2
Aiming to minimize service delay, we propose a new random caching scheme in device-to-device (D2D)-assisted heterogeneous network. To support diversified viewing qualities of multi…
Markovian approximation of the rough Bergomi model for Monte Carlo option pricing
Qinwen Zhu, Grégoire Loeper, Wen Chen +1
The recently developed rough Bergomi (rBergomi) model is a rough fractional stochastic volatility (RFSV) model which can generate more realistic term structure of at-the-money vola…
Recommendation Chart of Domains for Cross-Domain Sentiment Analysis:Findings of A 20 Domain Study
Akash Sheoran, Diptesh Kanojia, Aditya Joshi +1
Cross-domain sentiment analysis (CDSA) helps to address the problem of data scarcity in scenarios where labelled data for a domain (known as the target domain) is unavailable or in…