Combining Forecasts: A Genetic Programming Approach. - Adriano S. Koshiyama; Tatiana Escovedo; Douglas Mota Dias; Marley Maria Bernardes Rebuzzi Vellasco; Marco Aurélio Cavalcanti Pacheco (Int. J. Nat. Comput. Res., 2012)

GPF-CLASS: A Genetic Fuzzy model for classification. - Adriano S. Koshiyama; Tatiana Escovedo; Douglas Mota Dias; Marley M. B. R. Vellasco; Ricardo Tanscheit (IEEE Congress on Evolutionary Computation, 2013)

Numerical optimization by multi-gene genetic programming. - Adriano Soares Koshiyama; Douglas Mota Dias; André Vargas Abs da Cruz; Marco Aurélio Cavalcanti Pacheco (GECCO (Companion), 2013)

NEVE: A Neuro-Evolutionary Ensemble for Adaptive Learning. - Tatiana Escovedo; André Vargas Abs da Cruz; Marley Maria Bernardes Rebuzzi Vellasco; Adriano Soares Koshiyama (AIAI, 2013)

Using ensembles for adaptive learning: A comparative approach. - Tatiana Escovedo; André Vargas Abs da Cruz; Marley Maria Bernardes Rebuzzi Vellasco; Adriano S. Koshiyama (IJCNN, 2013)

Learning under Concept Drift using a Neuro-Evolutionary Ensemble. - Tatiana Escovedo; André Vargas Abs da Cruz; Marley Maria Bernardes Rebuzzi Vellasco; Adriano S. Koshiyama (Int. J. Comput. Intell. Appl., 2013)

Quantum-Inspired Multi-gene Linear Genetic Programming Model for Regression Problems. - Guilherme Cesário Strachan; Adriano S. Koshiyama; Douglas Mota Dias; Marley Maria Bernardes Rebuzzi Vellasco; Marco Aurélio Cavalcanti Pacheco (BRACIS, 2014)

GPFIS-Control: A fuzzy Genetic model for Control tasks. - Adriano S. Koshiyama; Tatiana Escovedo; Marley Maria Bernardes Rebuzzi Vellasco; Ricardo Tanscheit (FUZZ-IEEE, 2014)

Lithology discrimination using seismic elastic attributes: a genetic fuzzy classifier approach. - Eric da Silva Praxedes; Adriano S. Koshiyama; Elita Selmara Abreu; Douglas Mota Dias; Marley Maria Bernardes Rebuzzi Vellasco; Marco Aurélio Cavalcanti Pacheco (GECCO, 2014)

Towards a quantum-inspired multi-gene linear genetic programming model. - Guilherme Cesário Strachan; Adriano Soares Koshiyama; Douglas Mota Dias; Marley Maria Bernardes Rebuzzi Vellasco; Marco Aurélio Cavalcanti Pacheco (GECCO (Companion), 2014)

NEVE++: A neuro-evolutionary unlimited ensemble for adaptive learning. - Tatiana Escovedo; André Vargas Abs da Cruz; Adriano S. Koshiyama; Rubens Nascimento Melo; Marley Maria Bernardes Rebuzzi Vellasco (IJCNN, 2014)

Evolutionary features and parameter optimization of spiking neural networks for unsupervised learning. - Marco Silva 002; Adriano S. Koshiyama; Marley Maria Bernardes Rebuzzi Vellasco; Edson Cataldo (IJCNN, 2014)

GPFIS-Control: A Genetic Fuzzy System For Control Tasks. - Adriano S. Koshiyama; Marley M. B. R. Vellasco; Ricardo Tanscheit (J. Artif. Intell. Soft Comput. Res., 2014)

A Multi-gene Genetic Programming Fuzzy Inference System for Regression Problems. - Adriano S. Koshiyama; Marley M. B. R. Vellasco; Ricardo Tanscheit (IFSA-EUSFLAT, 2015)

Development of a fuzzy rule-based system using Genetic Programming for Forecasting problems. - Adriano S. Koshiyama; Marley M. B. R. Vellasco; Ricardo Tanscheit (FUZZ-IEEE, 2015)

A2D2: A pre-event abrupt drift detection. - Tatiana Escovedo; Adriano S. Koshiyama; Marley Maria Bernardes Rebuzzi Vellasco; Rubens Nascimento Melo; André Vargas Abs da Cruz (IJCNN, 2015)

GPFIS-CLASS: A Genetic Fuzzy System based on Genetic Programming for classification problems. - Adriano S. Koshiyama; Marley M. B. R. Vellasco; Ricardo Tanscheit (Appl. Soft Comput., 2015)

AutoMFIS: Fuzzy Inference System for multivariate time series forecasting. - Julio Ribeiro Coutinho; Ricardo Tanscheit; Marley M. B. R. Vellasco; Adriano S. Koshiyama (FUZZ-IEEE, 2016)

RandomFIS: A Fuzzy Classification System for Big Datasets. - Oscar Samudio; Marley M. B. R. Vellasco; Ricardo Tanscheit; Adriano S. Koshiyama (INNS Conference on Big Data, 2016)

Automatic Synthesis of Fuzzy Inference Systems for Classification. - Jorge Paredes; Ricardo Tanscheit; Marley M. B. R. Vellasco; Adriano S. Koshiyama (IPMU (1), 2016)

A Novel Genetic Fuzzy System for Regression Problems. - Adriano S. Koshiyama; Marley M. B. R. Vellasco; Ricardo Tanscheit (Fuzzy Technology, 2016)

Multi-Modal Optimization by Multi-Gene Genetic Programming. - Rogerio C. B. L. Povoa; Adriano S. Koshiyama; Douglas Mota Dias; Patricia L. Souza; Bruno A. C. Horta (CEC, 2018)

Mid-Curve Recommendation System: a Stacking Approach Through Neural Networks. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (IJCNN, 2018)

DetectA: abrupt concept drift detection in non-stationary environments. - Tatiana Escovedo; Adriano S. Koshiyama; André Vargas Abs da Cruz; Marley M. B. R. Vellasco (Appl. Soft Comput., 2018)

A Machine Learning-based Recommendation System for Swaptions Strategies. - Adriano Soares Koshiyama; Nick Firoozye; Philip C. Treleaven (CoRR, 2018)

Algorithms: Law and Regulation. - Philip C. Treleaven; Jeremy Barnett; Adriano S. Koshiyama (Computer, 2019)

Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (CoRR, 2019)

Augmenting correlation structures in spatial data using deep generative models. - Konstantin Klemmer; Adriano S. Koshiyama; Sebastian Flennerhag (CoRR, 2019)

A derivatives trading recommendation system: The mid-curve calendar spread case. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (Intell. Syst. Account. Finance Manag., 2019)

Assessing qualitative similarities between financial reporting frameworks using visualization and rules: COREP vs. pillar 3. - Wenmei Yang; Adriano S. Koshiyama (Intell. Syst. Account. Finance Manag., 2019)

Automatic synthesis of fuzzy systems: An evolutionary overview with a genetic programming perspective. - Adriano S. Koshiyama; Ricardo Tanscheit; Marley M. B. R. Vellasco (WIREs Data Mining Knowl. Discov., 2019)

Algorithms in future capital markets: a survey on AI, ML and associated algorithms in capital markets. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (ICAIF, 2020)

Neuroevolutionary learning in nonstationary environments. - Tatiana Escovedo; Adriano S. Koshiyama; André Vargas Abs da Cruz; Marley M. B. R. Vellasco (Appl. Intell., 2020)

QuantNet: Transferring Learning Across Systematic Trading Strategies. - Adriano S. Koshiyama; Sebastian Flennerhag; Stefano B. Blumberg; Nick Firoozye; Philip C. Treleaven (CoRR, 2020)

Unimodal optimization using a genetic-programming-based method with periodic boundary conditions. - Rogerio C. B. L. Povoa; Adriano S. Koshiyama; Douglas Mota Dias; Patricia L. Souza; Bruno A. C. Horta (Genet. Program. Evolvable Mach., 2020)

Applications of machine learning methods in financial markets. - Adriano Soares Koshiyama (2020)

AI auditing and impact assessment: according to the UK information commissioner's office. - Emre Kazim; Danielle Mendes Thame Denny; Adriano S. Koshiyama (AI Ethics, 2021)

Correction to: AI auditing and impact assessment: according to the UK information commissioner's office. - Emre Kazim; Danielle Mendes Thame Denny; Adriano S. Koshiyama (AI Ethics, 2021)

The interrelation between data and AI ethics in the context of impact assessments. - Emre Kazim; Adriano S. Koshiyama (AI Ethics, 2021)

Innovation and opportunity: review of the UK's national AI strategy. - Emre Kazim; Denise R. S. Almeida; Nigel Kingsman; Charles Kerrigan; Adriano S. Koshiyama; Elizabeth Lomas; Airlie Hilliard (Discov. Artif. Intell., 2021)

Machine Learning for Health: Algorithm Auditing & Quality Control. - Luis Oala; Andrew G. Murchison; Pradeep Balachandran; Shruti Choudhary; Jana Fehr; Alixandro Werneck Leite; Peter G. Goldschmidt; Christian Johner; Elora D. M. Schörverth; Rose Nakasi; Martin Meyer; Federico Cabitza; et al. (J. Medical Syst., 2021)

A high-level overview of AI ethics. - Emre Kazim; Adriano Soares Koshiyama (Patterns, 2021)

Algorithm Auditing: Managing the Legal, Ethical, and Technological Risks of Artificial Intelligence, Machine Learning, and Associated Algorithms. - Adriano Soares Koshiyama; Emre Kazim; Philip C. Treleaven (Computer, 2022)

Tacit knowledge elicitation process for industry 4.0. - Enzo Fenoglio; Emre Kazim; Hugo Latapie; Adriano S. Koshiyama (Discov. Artif. Intell., 2022)

Public sector AI transparency standard: UK Government seeks to lead by example. - Nigel Kingsman; Emre Kazim; Ali Chaudhry; Airlie Hilliard; Adriano S. Koshiyama; Roseline Polle; Giles Pavey; Umar Mohammed (Discov. Artif. Intell., 2022)

Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem. - Ethan Barrance; Emre Kazim; Airlie Hilliard; Markus Trengove; Sara Zannone; Adriano S. Koshiyama (Frontiers Artif. Intell., 2022)

On the sui generis value capture of new digital technologies: The case of AI. - Emre Kazim; Enzo Fenoglio; Airlie Hilliard; Adriano Soares Koshiyama; Catherine Mulligan; Markus Trengove; Abigail Gilbert; Arthur Gwagwa; Denise R. S. Almeida; Phil Godsiff; Kaska Porayska-Pomsta (Patterns, 2022)

Local Law 144: A Critical Analysis of Regression Metrics. - Giulio Filippi; Sara Zannone; Airlie Hilliard; Adriano S. Koshiyama (CoRR, 2023)

Uncovering Bias in Face Generation Models. - Cristian E. Muñoz; Sara Zannone; Umar Mohammed; Adriano S. Koshiyama (CoRR, 2023)

Local and Global Explainability Metrics for Machine Learning Predictions. - Cristian E. Muñoz; Kleyton da Costa; Bernardo Modenesi; Adriano S. Koshiyama (CoRR, 2023)

Intersectional Fairness: A Fractal Approach. - Giulio Filippi; Sara Zannone; Adriano S. Koshiyama (CoRR, 2023)

Towards Auditing Large Language Models: Improving Text-based Stereotype Detection. - Zekun Wu 003; Sahan Bulathwela; Adriano Soares Koshiyama (CoRR, 2023)

Proposed EU AI Act - Presidency compromise text: select overview and comment on the changes to the proposed regulation. - Emre Kazim; Osman Güçlütürk; Denise R. S. Almeida; Charles Kerrigan; Elizabeth Lomas; Adriano S. Koshiyama; Airlie Hilliard; Markus Trengove (AI Ethics, 2023)

JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models. - Ze Wang; Zekun Wu 003; Xin Guan; Michael Thaler; Adriano S. Koshiyama; Skylar Lu; Sachin Beepath; Ediz Ertekin Jr.; María Pérez-Ortiz 001 (EMNLP (Findings), 2024)

Investigating algorithmic bias in student progress monitoring. - Jamiu Adekunle Idowu; Adriano Soares Koshiyama; Philip C. Treleaven (Comput. Educ. Artif. Intell., 2024)

Eliciting Personality Traits in Large Language Models. - Airlie Hilliard; Cristian E. Muñoz; Zekun Wu 003; Adriano Soares Koshiyama (CoRR, 2024)

Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation. - Zekun Wu 003; Sahan Bulathwela; María Pérez-Ortiz 001; Adriano Soares Koshiyama (CoRR, 2024)

From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs. - Navya Jain; Zekun Wu 003; Cristian E. Muñoz; Airlie Hilliard; Adriano S. Koshiyama; Emre Kazim; Philip C. Treleaven (CoRR, 2024)

THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models. - Mengfei Liang; Archish Arun; Zekun Wu 003; Cristian E. Muñoz; Jonathan Lutch; Emre Kazim; Adriano S. Koshiyama; Philip C. Treleaven (CoRR, 2024)

HEARTS: A Holistic Framework for Explainable, Sustainable and Robust Text Stereotype Detection. - Theo King; Zekun Wu 003; Adriano S. Koshiyama; Emre Kazim; Philip C. Treleaven (CoRR, 2024)

Assessing Bias in Metric Models for LLM Open-Ended Generation Bias Benchmarks. - Nathaniel Demchak; Xin Guan; Zekun Wu 003; Ziyi Xu; Adriano S. Koshiyama; Emre Kazim (CoRR, 2024)

Bias Amplification: Language Models as Increasingly Biased Media. - Ze Wang; Zekun Wu 003; Jeremy Zhang; Navya Jain; Xin Guan; Adriano S. Koshiyama (CoRR, 2024)

SAGED: A Holistic Bias-Benchmarking Pipeline for Language Models with Customisable Fairness Calibration. - Xin Guan; Nathaniel Demchak; Saloni Gupta; Ze Wang; Ediz Ertekin Jr.; Adriano S. Koshiyama; Emre Kazim; Zekun Wu 003 (COLING, 2025)

From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs. - Navya Jain; Zekun Wu 003; Cristian E. Muñoz Villalobos; Airlie Hilliard; Xin Guan; Adriano S. Koshiyama; Emre Kazim; Philip C. Treleaven (NAACL (Findings), 2025)

HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications. - Rishi Kalra; Zekun Wu 003; Ayesha Gulley; Airlie Hilliard; Xin Guan; Adriano S. Koshiyama; Philip C. Treleaven (NAACL (Industry Track), 2025)

LibVulnWatch: A Deep Assessment Agent System and Leaderboard for Uncovering Hidden Vulnerabilities in Open-Source AI Libraries. - Zekun Wu 003; Seonglae Cho; Umar Mohammed; Cristian E. Muñoz; Kleyton da Costa; Xin Guan; Theo King; Ze Wang; Emre Kazim; Adriano S. Koshiyama (CoRR, 2025)

MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion. - Xin Guan; PeiHsin Lin; Zekun Wu 003; Ze Wang; Ruibo Zhang; Emre Kazim; Adriano S. Koshiyama (CoRR, 2025)

CorrSteer: Steering Improves Task Performance and Safety in LLMs through Correlation-based Sparse Autoencoder Feature Selection. - Seonglae Cho; Zekun Wu 003; Adriano S. Koshiyama (CoRR, 2025)