John Cartlidge

According to our database, John Cartlidge authored at least 40 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification.

Zinuo You, Pengju Zhang, Jin Zheng, John Cartlidge

CoRR, 2024

DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Prediction.

Zinuo You, Zijian Shi, Hongbo Bo, John Cartlidge, Li Zhang, Yan Ge

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

2023

Using Coevolution and Substitution of the Fittest for Health and Well-Being Recommender Systems.

Hugo Alcaraz-Herrera, John Cartlidge

SN Comput. Sci., May, 2023

Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks.

Lawrence Clegg, John Cartlidge

CoRR, 2023

Neural Stochastic Agent-Based Limit Order Book Simulation: A Hybrid Methodology.

Zijian Shi, John Cartlidge

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

EvoRecSys: Evolutionary framework for health and well-being recommender systems.

Hugo Alcaraz-Herrera, John Cartlidge, Zoi Toumpakari, Max Western, Iván Palomares

User Model. User Adapt. Interact., 2022

All for one and one for all: Fully decentralised privacy-preserving dark pool trading using multi-party computation.

Mariana Botelho da Gama, John Cartlidge, Nigel P. Smart, Younes Talibi Alaoui

IACR Cryptol. ePrint Arch., 2022

State Dependent Parallel Neural Hawkes Process for Limit Order Book Event Stream Prediction and Simulation.

Zijian Shi, John Cartlidge

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Exploration of Ontological Representations for Evolutionary Computation.

Hugo Alcaraz-Herrera, John Cartlidge

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

Challenges Faced by Industries and Their Potential Solutions in Deploying Machine Learning Applications.

Raj Mani Shukla, John Cartlidge

Proceedings of the 12th IEEE Annual Computing and Communication Workshop and Conference, 2022

2021

Multi-party computation mechanism for anonymous equity block trading: A secure implementation of turquoise plato uncross.

John Cartlidge, Nigel P. Smart, Younes Talibi Alaoui

Intell. Syst. Account. Finance Manag., 2021

Kicking-the-Bucket: Fast Privacy-Preserving Trading Using Buckets.

Mariana Botelho da Gama, John Cartlidge, Antigoni Polychroniadou, Nigel P. Smart, Younes Talibi Alaoui

IACR Cryptol. ePrint Arch., 2021

Geographical and temporal huff model calibration using taxi trajectory data.

Shuhui Gong, John Cartlidge, Ruibin Bai, Yang Yue, Qingquan Li, Guoping Qiu

GeoInformatica, 2021

The Limit Order Book Recreation Model (LOBRM): An Extended Analysis.

Zijian Shi, John Cartlidge

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021

Substitution of the Fittest: A Novel Approach for Mitigating Disengagement in Coevolutionary Genetic Algorithms.

Hugo Alcaraz-Herrera, John Cartlidge

Proceedings of the 13th International Joint Conference on Computational Intelligence, 2021

Block Auction: A General Blockchain Protocol for Privacy-Preserving and Verifiable Periodic Double Auctions.

Theodoros Constantinides, John Cartlidge

Proceedings of the 2021 IEEE International Conference on Blockchain, 2021

The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network.

Zijian Shi, Yu Chen, John Cartlidge

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Extracting activity patterns from taxi trajectory data: a two-layer framework using spatio-temporal clustering, Bayesian probability and Monte Carlo simulation.

Shuhui Gong, John Cartlidge, Ruibin Bai, Yang Yue, Qingquan Li, Guoping Qiu

Int. J. Geogr. Inf. Sci., 2020

Time Matters: Exploring the Effects of Urgency and Reaction Speed in Automated Traders.

Henry Hanifan, Ben Watson, John Cartlidge, Dave Cliff

Proceedings of the Agents and Artificial Intelligence, 12th International Conference, 2020

Fools Rush In: Competitive Effects of Reaction Time in Automated Trading.

Henry Hanifan, John Cartlidge

Proceedings of the 12th International Conference on Agents and Artificial Intelligence, 2020

2018

MPC Joins the Dark Side.

John Cartlidge, Nigel P. Smart, Younes Talibi Alaoui

IACR Cryptol. ePrint Arch., 2018

Optimisation of transportation service network using κ-node large neighbourhood search.

Ruibin Bai, John R. Woodward, Nachiappan Subramanian, John Cartlidge

Comput. Oper. Res., 2018

Agent-Based Model Exploration of Latency Arbitrage in Fragmented Financial Markets.

Matthew Duffin, John Cartlidge

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

2017

Geographical Huff Model Calibration using Taxi Trajectory Data.

Shuhui Gong, John Cartlidge, Yang Yue, Guoping Qiu, Qingquan Li, Jingyu Xin

Proceedings of the 10th ACM SIGSPATIAL Workshop on Computational Transportation Science, 2017

2014

Behavioural Investigations of Financial Trading Agents Using Exchange Portal (ExPo).

Steve Stotter, John Cartlidge, Dave Cliff

Trans. Comput. Collect. Intell., 2014

Correcting a financial brokerage model for cloud computing: closing the window of opportunity for commercialisation.

John Cartlidge, Philip Clamp

J. Cloud Comput., 2014

Trading Experiments using Financial Agents in a Simulated Cloud Computing Commodity Market.

John Cartlidge

Proceedings of the ICAART 2014, 2014

2013

Exploring Assignment-Adaptive (ASAD) Trading Agents in Financial Market Experiments.

Steve Stotter, John Cartlidge, Dave Cliff

Proceedings of the ICAART 2013, 2013

Evidencing the "Robot Phase Transition" in Human-agent Experimental Financial Markets.

John Cartlidge, Dave Cliff

Proceedings of the ICAART 2013, 2013

Comparison of Cloud Middleware Protocols and Subscription Network Topologies using CReST, the Cloud Research Simulation Toolkit - The Three Truths of Cloud Computing are: Hardware Fails, Software has Bugs, and People Make Mistakes.

John Cartlidge, Dave Cliff

Proceedings of the CLOSER 2013, 2013

Flying by the seat of their pants: what can high frequency trading learn from aviation?

Gordon D. Baxter, John Cartlidge

Proceedings of the International Conference on Application and Theory of Automation in Command and Control Systems, 2013

2012

Too Fast Too Furious - Faster Financial-market Trading Agents Can Give Less Efficient Markets.

John Cartlidge, Charlotte Szostek, Marco De Luca, Dave Cliff

Proceedings of the ICAART 2012 - Proceedings of the 4th International Conference on Agents and Artificial Intelligence, Volume 2, 2012

2011

Autonomous Virulence Adaptation Improves Coevolutionary Optimization.

John Cartlidge, Djamel Ait-Boudaoud

IEEE Trans. Evol. Comput., 2011

Modelling Resilience in Cloud-Scale Data Centres

John Cartlidge, Ilango Sriram

CoRR, 2011

2008

Dynamically adapting parasite virulence to combat coevolutionary disengagement.

John Cartlidge

Proceedings of the Eleventh International Conference on the Synthesis and Simulation of Living Systems, 2008

2004

Rules of engagement : competitive coevolutionary dynamics in computational systems.

John Cartlidge

PhD thesis, 2004

Combating Coevolutionary Disengagement by Reducing Parasite Virulence.

John Cartlidge, Seth Bullock

Evol. Comput., 2004

Unpicking Tartan CIAO Plots: Understanding Irregular Coevolutionary Cycling.

John Cartlidge, Seth Bullock

Adapt. Behav., 2004

2003

Caring versus Sharing: How to Maintain Engagement and Diversity in Coevolving Populations.

John Cartlidge, Seth Bullock

Proceedings of the Advances in Artificial Life, 7th European Conference, 2003

2002

Learning lessons from the common cold: How reducing parasite virulence improves coevolutionary optimization.

John Cartlidge, Seth Bullock

Proceedings of the 2002 Congress on Evolutionary Computation, 2002