Adriano S. Koshiyama

According to our database, Adriano S. Koshiyama authored at least 63 papers between 2012 and 2024.

Collaborative distances:

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

2024

Bias Amplification: Language Models as Increasingly Biased Media.

Ze Wang, Zekun Wu, Jeremy Zhang, Navya Jain, Xin Guan, Adriano S. Koshiyama

CoRR, 2024

Assessing Bias in Metric Models for LLM Open-Ended Generation Bias Benchmarks.

Nathaniel Demchak, Xin Guan, Zekun Wu, Ziyi Xu, Adriano S. Koshiyama, Emre Kazim

CoRR, 2024

HEARTS: A Holistic Framework for Explainable, Sustainable and Robust Text Stereotype Detection.

Theo King, Zekun Wu, 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, Cristian Muñoz, Jonathan Lutch, Emre Kazim, Adriano S. Koshiyama, Philip C. Treleaven

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

CoRR, 2024

From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs.

Navya Jain, Zekun Wu, Cristian Muñoz, Airlie Hilliard, Adriano S. Koshiyama, Emre Kazim, Philip C. Treleaven

CoRR, 2024

HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications.

Rishi Kalra, Zekun Wu, Ayesha Gulley, Airlie Hilliard, Xin Guan, Adriano S. Koshiyama, Philip C. Treleaven

CoRR, 2024

Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation.

Zekun Wu, Sahan Bulathwela, María Pérez-Ortiz, Adriano Soares Koshiyama

CoRR, 2024

Eliciting Personality Traits in Large Language Models.

Airlie Hilliard, Cristian Muñoz, Zekun Wu, Adriano Soares Koshiyama

CoRR, 2024

JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models.

Ze Wang, Zekun Wu, Xin Guan, Michael Thaler, Adriano S. Koshiyama, Skylar Lu, Sachin Beepath, Ediz Ertekin Jr., María Pérez-Ortiz

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

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, May, 2023

Towards Auditing Large Language Models: Improving Text-based Stereotype Detection.

Zekun Wu, Sahan Bulathwela, Adriano Soares Koshiyama

CoRR, 2023

Intersectional Fairness: A Fractal Approach.

Giulio Filippi, Sara Zannone, Adriano S. Koshiyama

CoRR, 2023

Local and Global Explainability Metrics for Machine Learning Predictions.

Cristian Muñoz, Kleyton da Costa, Bernardo Modenesi, Adriano S. Koshiyama

CoRR, 2023

Uncovering Bias in Face Generation Models.

Cristian Muñoz, Sara Zannone, Umar Mohammed, Adriano S. Koshiyama

CoRR, 2023

Local Law 144: A Critical Analysis of Regression Metrics.

Giulio Filippi, Sara Zannone, Airlie Hilliard, Adriano S. Koshiyama

CoRR, 2023

2022

On the <i>sui generis</i> 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

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

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

Tacit knowledge elicitation process for industry 4.0.

Enzo Fenoglio, Emre Kazim, Hugo Latapie, Adriano S. Koshiyama

Discov. Artif. Intell., 2022

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

2021

A high-level overview of AI ethics.

Emre Kazim, Adriano Soares Koshiyama

Patterns, 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, Pat D. Baird, Carolin Prabhu, Eva Weicken, Xiaoxuan Liu, Markus Wenzel, Steffen Vogler, Darlington Ahiale Akogo, Shada Alsalamah, Emre Kazim, Adriano S. Koshiyama, Sven Piechottka, Sheena Macpherson, Ian Shadforth, Regina Geierhofer, Christian Matek, Joachim Krois, Bruno Sanguinetti, Matthew Arentz, Pavol Bielik, Saúl Calderón Ramírez, Auss Abbood, Nicolas Langer, Stefan Haufe, Ferath Kherif, Sameer Pujari, Wojciech Samek, Thomas Wiegand

J. Medical Syst., 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

The interrelation between data and AI ethics in the context of impact assessments.

Emre Kazim, 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

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

2020

Applications of machine learning methods in financial markets.

Adriano Soares Koshiyama

PhD thesis, 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

QuantNet: Transferring Learning Across Systematic Trading Strategies.

Adriano S. Koshiyama, Sebastian Flennerhag, Stefano B. Blumberg, Nick Firoozye, Philip C. Treleaven

CoRR, 2020

Neuroevolutionary learning in nonstationary environments.

Tatiana Escovedo, Adriano S. Koshiyama, André Vargas Abs da Cruz, Marley M. B. R. Vellasco

Appl. Intell., 2020

Algorithms in future capital markets: a survey on AI, ML and associated algorithms in capital markets.

Adriano S. Koshiyama, Nick Firoozye, Philip C. Treleaven

Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

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

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

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

Augmenting correlation structures in spatial data using deep generative models.

Konstantin Klemmer, Adriano S. Koshiyama, Sebastian Flennerhag

CoRR, 2019

Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination.

Adriano S. Koshiyama, Nick Firoozye, Philip C. Treleaven

CoRR, 2019

Algorithms: Law and Regulation.

Philip C. Treleaven, Jeremy Barnett, Adriano S. Koshiyama

Computer, 2019

2018

A Machine Learning-based Recommendation System for Swaptions Strategies.

Adriano Soares Koshiyama, Nick Firoozye, Philip C. Treleaven

CoRR, 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

Mid-Curve Recommendation System: a Stacking Approach Through Neural Networks.

Adriano S. Koshiyama, Nick Firoozye, Philip C. Treleaven

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

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

Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2016

A Novel Genetic Fuzzy System for Regression Problems.

Adriano S. Koshiyama, Marley M. B. R. Vellasco, Ricardo Tanscheit

Proceedings of the Fuzzy Technology - Present Applications and Future Challenges, 2016

Automatic Synthesis of Fuzzy Inference Systems for Classification.

Jorge Paredes, Ricardo Tanscheit, Marley M. B. R. Vellasco, Adriano S. Koshiyama

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

RandomFIS: A Fuzzy Classification System for Big Datasets.

Oscar Samudio, Marley M. B. R. Vellasco, Ricardo Tanscheit, Adriano S. Koshiyama

Proceedings of the Advances in Big Data, 2016

AutoMFIS: Fuzzy Inference System for multivariate time series forecasting.

Julio Ribeiro Coutinho, Ricardo Tanscheit, Marley M. B. R. Vellasco, Adriano S. Koshiyama

Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, 2016

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

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

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Development of a fuzzy rule-based system using Genetic Programming for Forecasting problems.

Adriano S. Koshiyama, Marley M. B. R. Vellasco, Ricardo Tanscheit

Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, 2015

A Multi-gene Genetic Programming Fuzzy Inference System for Regression Problems.

Adriano S. Koshiyama, Marley M. B. R. Vellasco, Ricardo Tanscheit

Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15), 2015

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

Evolutionary features and parameter optimization of spiking neural networks for unsupervised learning.

Marco Silva, Adriano S. Koshiyama, Marley Maria Bernardes Rebuzzi Vellasco, Edson Cataldo

Proceedings of the 2014 International Joint Conference on Neural Networks, 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

Proceedings of the 2014 International Joint Conference on Neural Networks, 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

Proceedings of the Genetic and Evolutionary Computation Conference, 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

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

GPFIS-Control: A fuzzy Genetic model for Control tasks.

Adriano S. Koshiyama, Tatiana Escovedo, Marley Maria Bernardes Rebuzzi Vellasco, Ricardo Tanscheit

Proceedings of the IEEE International Conference on Fuzzy Systems, 2014

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

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

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

Using ensembles for adaptive learning: A comparative approach.

Tatiana Escovedo, André Vargas Abs da Cruz, Marley Maria Bernardes Rebuzzi Vellasco, Adriano S. Koshiyama

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

NEVE: A Neuro-Evolutionary Ensemble for Adaptive Learning.

Tatiana Escovedo, André Vargas Abs da Cruz, Marley Maria Bernardes Rebuzzi Vellasco, Adriano Soares Koshiyama

Proceedings of the Artificial Intelligence Applications and Innovations, 2013

Numerical optimization by multi-gene genetic programming.

Adriano Soares Koshiyama, Douglas Mota Dias, André Vargas Abs da Cruz, Marco Aurélio Cavalcanti Pacheco

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

GPF-CLASS: A Genetic Fuzzy model for classification.

Adriano S. Koshiyama, Tatiana Escovedo, Douglas Mota Dias, Marley M. B. R. Vellasco, Ricardo Tanscheit

Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2012

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