95 citations · 160 across the 14 of their papers we have counts for
4 papers · 2 filters
Learning population and subject-specific brain connectivity networks via Mixed Neighborhood Selection
Ricardo Pio Monti, Christoforos Anagnostopoulos, Giovanni Montana
In neuroimaging data analysis, Gaussian graphical models are often used to model statistical dependencies across spatially remote brain regions known as functional connectivity. Ty…
Streaming regularization parameter selection via stochastic gradient descent
Ricardo Pio Monti, Romy Lorenz, Robert Leech +2
We propose a framework to perform streaming covariance selection. Our approach employs regularization constraints where a time-varying sparsity parameter is iteratively estimated v…
Measuring the functional connectome "on-the-fly": towards a new control signal for fMRI-based brain-computer interfaces
Ricardo Pio Monti, Romy Lorenz, Christoforos Anagnostopoulos +2
There has been an explosion of interest in functional Magnetic Resonance Imaging (MRI) during the past two decades. Naturally, this has been accompanied by many major advances in t…
Estimating Optimal Active Learning via Model Retraining Improvement
Lewis P. G. Evans, Niall M. Adams, Christoforos Anagnostopoulos
A central question for active learning (AL) is: "what is the optimal selection?" Defining optimality by classifier loss produces a new characterisation of optimal AL behaviour, by…