252 citations · 292 across the 20 of their papers we have counts for
20 papers
Integrated Private Data Trading Systems for Data Marketplaces
Weidong Li, Mengxiao Zhang, Libo Zhang +1
In the digital age, data is a valuable commodity, and data marketplaces offer lucrative opportunities for data owners to monetize their private data. However, data privacy is a sig…
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
Qiming Bao, Alex Yuxuan Peng, Zhenyun Deng +10
Combining large language models with logical reasoning enhances their capacity to address problems in a robust and reliable manner. Nevertheless, the intricate nature of logical re…
A Survey of Data Pricing for Data Marketplaces
Mengxiao Zhang, Fernando Beltran, Jiamou Liu
A data marketplace is an online venue that brings data owners, data brokers, and data consumers together and facilitates commoditisation of data amongst them. Data pricing, as a ke…
GETNext: Trajectory Flow Map Enhanced Transformer for Next POI Recommendation
Song Yang, Jiamou Liu, Kaiqi Zhao
Next POI recommendation intends to forecast users' immediate future movements given their current status and historical information, yielding great values for both users and servic…
Learning Density-Based Correlated Equilibria for Markov Games
Libo Zhang, Yang Chen, Toru Takisaka +3
Correlated Equilibrium (CE) is a well-established solution concept that captures coordination among agents and enjoys good algorithmic properties. In real-world multi-agent systems…
Differentially Private Diffusion Auction: The Single-unit Case
Fengjuan Jia, Mengxiao Zhang, Jiamou Liu +1
Diffusion auction refers to an emerging paradigm of online marketplace where an auctioneer utilises a social network to attract potential buyers. Diffusion auction poses significan…
USER: Unsupervised Structural Entropy-based Robust Graph Neural Network
Yifei Wang, Yupan Wang, Zeyu Zhang +3
Unsupervised/self-supervised graph neural networks (GNN) are vulnerable to inherent randomness in the input graph data which greatly affects the performance of the model in downstr…
MSDC: Exploiting Multi-State Power Consumption in Non-intrusive Load Monitoring based on A Dual-CNN Model
Jialing He, Jiamou Liu, Zijian Zhang +4
Non-intrusive load monitoring (NILM) aims to decompose aggregated electrical usage signal into appliance-specific power consumption and it amounts to a classical example of blind s…
Multi-unit Auction over a Social Network
Yuan Fang, Mengxiao Zhang, Jiamou Liu +2
Diffusion auction is an emerging business model where a seller aims to incentivise buyers in a social network to diffuse the auction information thereby attracting potential buyers…
Centralization Problem for Opinion Convergence in Decentralized Networks
Yiping Liu, Jiamou Liu, Bakhadyr Khoussaino +2
This paper aims to provide a new perspective on the interplay between decentralization -- a prevalent character of multi-agent systems -- and centralization, i.e., the task of impo…
Constrained Few-Shot Learning: Human-Like Low Sample Complexity Learning and Non-Episodic Text Classification
Jaron Mar, Jiamou Liu
Few-shot learning (FSL) is an emergent paradigm of learning that attempts to learn to reason with low sample complexity to mimic the way humans learn, generalise and extrapolate fr…
Multi-Step Deductive Reasoning Over Natural Language: An Empirical Study on Out-of-Distribution Generalisation
Qiming Bao, Alex Yuxuan Peng, Tim Hartill +4
Combining deep learning with symbolic logic reasoning aims to capitalize on the success of both fields and is drawing increasing attention. Inspired by DeepLogic, an end-to-end mod…
From Cognitive to Computational Modeling: Text-based Risky Decision-Making Guided by Fuzzy Trace Theory
Jaron Mar, Jiamou Liu
Understanding, modelling and predicting human risky decision-making is challenging due to intrinsic individual differences and irrationality. Fuzzy trace theory (FTT) is a powerful…
Individual-Level Inverse Reinforcement Learning for Mean Field Games
Yang Chen, Libo Zhang, Jiamou Liu +1
The recent mean field game (MFG) formalism has enabled the application of inverse reinforcement learning (IRL) methods in large-scale multi-agent systems, with the goal of inferrin…
GACAN: Graph Attention-Convolution-Attention Networks for Traffic Forecasting Based on Multi-granularity Time Series
Sikai Zhang, Hong Zheng, Hongyi Su +3
Traffic forecasting is an integral part of intelligent transportation systems (ITS). Achieving a high prediction accuracy is a challenging task due to a high level of dynamics and…
Space Meets Time: Local Spacetime Neural Network For Traffic Flow Forecasting
Song Yang, Jiamou Liu, Kaiqi Zhao
Traffic flow forecasting is a crucial task in urban computing. The challenge arises as traffic flows often exhibit intrinsic and latent spatio-temporal correlations that cannot be…
Generating Relevant and Coherent Dialogue Responses using Self-separated Conditional Variational AutoEncoders
Bin Sun, Shaoxiong Feng, Yiwei Li +2
Conditional Variational AutoEncoder (CVAE) effectively increases the diversity and informativeness of responses in open-ended dialogue generation tasks through enriching the contex…
THINK: A Novel Conversation Model for Generating Grammatically Correct and Coherent Responses
Bin Sun, Shaoxiong Feng, Yiwei Li +2
Many existing conversation models that are based on the encoder-decoder framework have focused on ways to make the encoder more complicated to enrich the context vectors so as to i…
Adversarial Inverse Reinforcement Learning for Mean Field Games
Yang Chen, Libo Zhang, Jiamou Liu +1
Mean field games (MFGs) provide a mathematically tractable framework for modelling large-scale multi-agent systems by leveraging mean field theory to simplify interactions among ag…
Selling Data at an Auction under Privacy Constraints
Mengxiao Zhang, Fernando Beltran, Jiamou Liu
Private data query combines mechanism design with privacy protection to produce aggregated statistics from privately-owned data records. The problem arises in a data marketplace wh…