17 citations · 67 across the 16 of their papers we have counts for
16 papers
SCONE-GAN: Semantic Contrastive learning-based Generative Adversarial Network for an end-to-end image translation
Iman Abbasnejad, Fabio Zambetta, Flora Salim +4
SCONE-GAN presents an end-to-end image translation, which is shown to be effective for learning to generate realistic and diverse scenery images. Most current image-to-image transl…
i-Align: an interpretable knowledge graph alignment model
Bayu Distiawan Trisedya, Flora D Salim, Jeffrey Chan +3
Knowledge graphs (KGs) are becoming essential resources for many downstream applications. However, their incompleteness may limit their potential. Thus, continuous curation is need…
Are footpaths encroached by shared e-scooters? Spatio-temporal Analysis of Micro-mobility Services
Hiruni Kegalle, Danula Hettiachchi, Jeffrey Chan +2
Micro-mobility services (e.g., e-bikes, e-scooters) are increasingly popular among urban communities, being a flexible transport option that brings both opportunities and challenge…
Measuring disentangled generative spatio-temporal representation
Sichen Zhao, Wei Shao, Jeffrey Chan +1
Disentangled representation learning offers useful properties such as dimension reduction and interpretability, which are essential to modern deep learning approaches. Although dee…
MoParkeR : Multi-objective Parking Recommendation
Mohammad Saiedur Rahaman, Wei Shao, Flora D. Salim +5
Existing parking recommendation solutions mainly focus on finding and suggesting parking spaces based on the unoccupied options only. However, there are other factors associated wi…
Learning Vehicle Routing Problems using Policy Optimisation
Nasrin Sultana, Jeffrey Chan, A. K. Qin +1
Deep reinforcement learning (DRL) has been used to learn effective heuristics for solving complex combinatorial optimisation problem via policy networks and have demonstrated promi…
Divide and Learn: A Divide and Conquer Approach for Predict+Optimize
Ali Ugur Guler, Emir Demirovic, Jeffrey Chan +3
The predict+optimize problem combines machine learning ofproblem coefficients with a combinatorial optimization prob-lem that uses the predicted coefficients. While this problemcan…
Learning to Optimise General TSP Instances
Nasrin Sultana, Jeffrey Chan, A. K. Qin +1
The Travelling Salesman Problem (TSP) is a classical combinatorial optimisation problem. Deep learning has been successfully extended to meta-learning, where previous solving effor…
Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors
Manpreet Kaur, Flora D. Salim, Yongli Ren +3
This paper investigates the Cyber-Physical behavior of users in a large indoor shopping mall by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the m…
Less is More: Rejecting Unreliable Reviews for Product Question Answering
Shiwei Zhang, Xiuzhen Zhang, Jey Han Lau +2
Promptly and accurately answering questions on products is important for e-commerce applications. Manually answering product questions (e.g. on community question answering platfor…
MurTree: Optimal Classification Trees via Dynamic Programming and Search
Emir Demirović, Anna Lukina, Emmanuel Hebrard +5
Decision tree learning is a widely used approach in machine learning, favoured in applications that require concise and interpretable models. Heuristic methods are traditionally us…
An Ambient-Physical System to Infer Concentration in Open-plan Workplace
Mohammad Saiedur Rahaman, Jonathan Liono, Yongli Ren +4
One of the core challenges in open-plan workspaces is to ensure a good level of concentration for the workers while performing their tasks. Hence, being able to infer concentration…
Flight Delay Prediction using Airport Situational Awareness Map
Wei Shao, Arian Prabowo, Sichen Zhao +6
The prediction of flight delays plays a significantly important role for airlines and travelers because flight delays cause not only tremendous economic loss but also potential sec…
Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network
Wei Shao, Flora D. Salim, Jeffrey Chan +2
Deep learning has been extended to a number of new domains with critical success, though some traditional orienteering problems such as the Travelling Salesman Problem (TSP) and it…
Ground Truth Bias in External Cluster Validity Indices
Yang Lei, James C. Bezdek, Simone Romano +3
It has been noticed that some external CVIs exhibit a preferential bias towards a larger or smaller number of clusters which is monotonic (directly or inversely) in the number of c…
MOOCs Meet Measurement Theory: A Topic-Modelling Approach
Jiazhen He, Benjamin I. P. Rubinstein, James Bailey +3
This paper adapts topic models to the psychometric testing of MOOC students based on their online forum postings. Measurement theory from education and psychology provides statisti…