Recent publications
Article
Eryilmaz, OB, Katar, C & Little, MA 2026, 'Flow-aware ellipsoidal filtration for persistent homology of recurrent signals', Chaos, vol. 36, no. 3, 033140. https://doi.org/10.1063/5.0317749
Evers, LJW, Raykov, YP, Heskes, TM, Krijthe, JH, Bloem, BR & Little, MA 2025, 'Passive Monitoring of Parkinson Tremor in Daily Life: A Prototypical Network Approach', Sensors, vol. 25, no. 2, 366. https://doi.org/10.3390/s25020366
Post, E, Laarhoven, TV, Raykov, YP, Little, MA, Nonnekes, J, Heskes, TM, Bloem, BR & Evers, LJW 2025, 'Quantifying arm swing in Parkinson’s disease: a method accounting for arm activities during free-living gait', Journal of neuroengineering and rehabilitation, vol. 22, no. 1, 22. https://doi.org/10.1186/s12984-025-01578-z
Farooq, A, Raykov, YP, Raykov, P & Little, MA 2024, 'Adaptive Latent Feature Sharing for Piecewise Linear Dimensionality Reduction', Journal of Machine Learning Research, vol. 25, no. 135, pp. 1-42. <http://jmlr.org/papers/v25/21-0146.html>
Conference contribution
He, X & Little, M 2026, An efficient, provably optimal algorithm for the 0-1 loss linear classification problem. in C Vondrick, B Hariharan, C Raffel, L Pinto, D Yang & A Faust (eds), The Fourteenth International Conference on Learning Representations: ICLR 2026. International Conference on Learning Representations, ICLR, Fourteenth International Conference on Learning Representations, Rio de Janeiro, Brazil, 23/04/26.
Aloyayri, AA, Little, MA & Zakar, NA 2026, Causal Analysis of Parkinson's Motor Symptoms Using Structured Smartphone Accelerometer Data. in Artificial Intelligence in Healthcare: Third International Conference, AIiH 2026, London, UK, August 26–28, 2026, Proceedings. 1st edn, Lecture Notes in Computer Science, Springer, Cham, Third International Conference on AI in Healthcare 2026, London, United Kingdom, 26/08/26.
He, X, Miao, Y & Little, M 2026, Deep-ICE: The first globally optimal algorithm for empirical risk minimization of two-layer maxout and ReLU networks. in The Fourteenth International Conference on Learning Representations: ICLR 2026. International Conference on Learning Representations, ICLR, Fourteenth International Conference on Learning Representations, Rio de Janeiro, Brazil, 23/04/26.
Eryilmaz, O, Katar, C & Little, M 2025, Ellipsoidal Filtration for Topological Denoising of Recurrent Signals. in 2025 International Symposium on Nonlinear Theory and Its Applications. IEICE proceeding series, Institute of Electronics, Information and Communication Engineers, pp. 610-613, The 2025 International Symposium on Nonlinear Theory and Its Applications , Okinawa, Japan, 27/10/25. <https://arxiv.org/abs/2510.16682>
Poster
Mao, J & Little, M 2026, 'A Deconfounding Method for Reverse Causal Inference Using Causally Weighted Gaussian Mixture Models', HDR UK Early Career Researcher (ECR) Conference 2026, London, United Kingdom, 21/04/26 - 21/04/26.
Mao, J & Little, M 2026, 'A Weighted Resampling Framework for Causal Transportability', EUROPEAN CAUSAL INFERENCE MEETING 2026, Oxford, United Kingdom, 15/04/26 - 17/04/26.
Zakar, N, Aloyayri, A & Little, M 2026, 'Causal Identification via DAG and ADMG Simplification in Wearable Parkinson’s Disease Studies', EUROPEAN CAUSAL INFERENCE MEETING 2026, Oxford, United Kingdom, 15/04/26 - 17/04/26.
Zakar, N, Aloyayri, A & Little, M 2026, 'Causal Identification via DAG Simplification in Wearable Parkinson's Disease Studies', Third International Conference on AI in Healthcare 2026, London, United Kingdom, 26/08/26 - 28/08/26.
Eryilmaz, O, Katar, C & Little, M 2025, 'Ellipsoidal Filtration for Topological Denoising of Quasi-Periodic Signals', Dynamics Days Europe 2025, Thessaloniki, Greece, 23/06/25 - 27/06/25.
Preprint
Mao, J & Little, MA 2025 'Front-door Reducibility: Reducing ADMGs to the Standard Front-door Setting via a Graphical Criterion' arXiv. https://doi.org/10.48550/arXiv.2511.15679
Mao, J & Little, MA 2024 'Mechanism Learning: reverse causal inference in the presence of multiple unknown confounding through causally weighted Gaussian mixture models' arXiv. https://doi.org/10.48550/arXiv.2410.20057
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