Online optimization for variable selection in data streams. - Christoforos Anagnostopoulos; Dimitris K. Tasoulis; David J. Hand; Niall M. Adams (ECAI, 2008)

Deciding what to observe next: adaptive variable selection for regression in multivariate data streams. - Christoforos Anagnostopoulos; Niall M. Adams; David J. Hand (SAC, 2008)

Simulating Dynamic Covariance Structures for Testing the Adaptive Behavior of Variable Selection Algorithms. - Christoforos Anagnostopoulos; Niall M. Adams (UKSim, 2008)

Temporally adaptive estimation of logistic classifiers on data streams. - Christoforos Anagnostopoulos; Dimitris K. Tasoulis; Niall M. Adams; David J. Hand (Adv. Data Anal. Classif., 2009)

Temporally-Adaptive Linear Classification for Handling Population Drift in Credit Scoring. - Niall M. Adams; Dimitris K. Tasoulis; Christoforos Anagnostopoulos; David J. Hand (COMPSTAT, 2010)

Streaming Covariance Selection with Applications to Adaptive Querying in Sensor Networks. - Christoforos Anagnostopoulos; Niall M. Adams; David J. Hand (Comput. J., 2010)

Online linear and quadratic discriminant analysis with adaptive forgetting for streaming classification. - Christoforos Anagnostopoulos; Dimitris K. Tasoulis; Niall M. Adams; Nicos G. Pavlidis; David J. Hand (Stat. Anal. Data Min., 2012)

When Does Active Learning Work? - Lewis Percival Gordon Evans; Niall M. Adams; Christoforos Anagnostopoulos (IDA, 2013)

Information-Theoretic Data Discarding for Dynamic Trees on Data Streams. - Christoforos Anagnostopoulos; Robert B. Gramacy (Entropy, 2013)

When is the area under the receiver operating characteristic curve an appropriate measure of classifier performance? - David J. Hand; Christoforos Anagnostopoulos (Pattern Recognit. Lett., 2013)

Targeting Optimal Active Learning via Example Quality. - Lewis Percival Gordon Evans; Niall M. Adams; Christoforos Anagnostopoulos (CoRR, 2014)

Estimating time-varying brain connectivity networks from functional MRI time series. - Ricardo Pio Monti; Peter Hellyer; David J. Sharp; Robert Leech; Christoforos Anagnostopoulos; Giovanni Montana (NeuroImage, 2014)

A better Beta for the H measure of classification performance. - David J. Hand; Christoforos Anagnostopoulos (Pattern Recognit. Lett., 2014)

Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data. - Ricardo Pio Monti; Romy Lorenz; Peter Hellyer; Robert Leech; Christoforos Anagnostopoulos; Giovanni Montana (PRNI, 2015)

Estimating Optimal Active Learning via Model Retraining Improvement. - Lewis Percival Gordon Evans; Niall M. Adams; Christoforos Anagnostopoulos (CoRR, 2015)

Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization. - Romy Lorenz; Ricardo Pio Monti; Adam Hampshire; Yury Koush; Christoforos Anagnostopoulos; Aldo A. Faisal; David J. Sharp; Giovanni Montana; Robert Leech; Inês R. Violante (PRNI, 2016)

Text-mining the neurosynth corpus using deep boltzmann machines. - Ricardo Pio Monti; Romy Lorenz; Robert Leech; Christoforos Anagnostopoulos; Giovanni Montana (PRNI, 2016)

A framework for adaptive regularization in streaming Lasso models. - Ricardo Pio Monti; Christoforos Anagnostopoulos; Giovanni Montana (CoRR, 2016)

The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI. - Romy Lorenz; Ricardo Pio Monti; Inês R. Violante; Christoforos Anagnostopoulos; Aldo A. Faisal; Giovanni Montana; Robert Leech (NeuroImage, 2016)

Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods. - Ricardo Pio Monti; Romy Lorenz; Peter Hellyer; Robert Leech; Christoforos Anagnostopoulos; Giovanni Montana (Frontiers Comput. Neurosci., 2017)

Adaptive regularization for Lasso models in the context of nonstationary data streams. - Ricardo Pio Monti; Christoforos Anagnostopoulos; Giovanni Montana (Stat. Anal. Data Min., 2018)

Notes on the H-measure of classifier performance. - David J. Hand; Christoforos Anagnostopoulos (Adv. Data Anal. Classif., 2023)