21 citations · 47 across the 15 of their papers we have counts for
17 papers
Semi-supervised Hopfield model: Theoretical and Numerical results
Linda Albanese, Andrea Ladiana, Andrea Lepre
In the daily practice of Machine Learning, fully labeled datasets are a luxury: labels demand expensive and time-consuming human annotation, whereas raw, unlabeled data can be harv…
Partial annealing and pattern decorrelation in associative neural networks
Linda Albanese, Andrea Alessandrelli, Adriano Barra +2
Using the Hopfield model as a benchmark case, the present work focuses on the investigation of partially annealed associative neural networks, wherein neural dynamics is coupled to…
Dense Associative Memory with biased patterns: a Replica Symmetric analysis
Linda Albanese, Andrea Alessandrelli, Federico Carella
We investigate dense higher-order associative memories in the high storage regime when the stored patterns are biased, namely when the entries of the patterns are not symmetrically…
Serial vs parallel recall in the Blume-Every-Griffiths neural networks
Linda Albanese, Andrea Alessandrelli, Adriano Barra +1
Fully connected Blume-Emery-Griffiths neural networks performing pattern recognition and associative memory have been heuristically studied in the past (mainly via the replica tric…
Yet another exponential Hopfield model
Linda Albanese, Andrea Alessandrelli, Adriano Barra +1
We propose and analyze a new variation of the so-called {\em exponential Hopfield model}, a recently introduced family of associative neural networks with unprecedented storage cap…
Guerra interpolation for inverse freezing
Linda Albanese, Adriano Barra, Emilio N. M. Cirillo
In these short notes, we adapt and systematically apply Guerra's interpolation techniques on a class of disordered mean-field spin glasses equipped with crystal fields and multi-va…
Boolean SK Model
Linda Albanese, Andrea Alessandrelli
For over half a century, statistical mechanics of spin glasses played as a paradigm to model and interpret disparate phenomena, ranging from quantitative biology to computer scienc…
About the AT line in Replica Symmetry Breaking assumption for spin glasses
Linda Albanese
Replica Symmetry Breaking is a fascinating phenomenon of spin glasses model which could have consequences also in other field of studies. Although there are several studies regardi…
Hebbian Learning from First Principles
Linda Albanese, Adriano Barra, Pierluigi Bianco +2
Recently, the original storage prescription for the Hopfield model of neural networks -- as well as for its dense generalizations -- has been turned into a genuine Hebbian learning…
Unsupervised and Supervised learning by Dense Associative Memory under replica symmetry breaking
Linda Albanese, Andrea Alessandrelli, Alessia Annibale +1
Statistical mechanics of spin glasses is one of the main strands toward a comprehension of information processing by neural networks and learning machines. Tackling this approach,…
About the de Almeida-Thouless line in neural networks
Linda Albanese, Andrea Alessandrelli, Adriano Barra +1
In this work we present a rigorous and straightforward method to detect the onset of the instability of replica-symmetric theories in information processing systems, which does not…
Dense Hebbian neural networks: a replica symmetric picture of supervised learning
Elena Agliari, Linda Albanese, Francesco Alemanno +5
We consider dense, associative neural-networks trained by a teacher (i.e., with supervision) and we investigate their computational capabilities analytically, via statistical-mecha…
Dense Hebbian neural networks: a replica symmetric picture of unsupervised learning
Elena Agliari, Linda Albanese, Francesco Alemanno +5
We consider dense, associative neural-networks trained with no supervision and we investigate their computational capabilities analytically, via a statistical-mechanics approach, a…
Replica symmetry breaking in dense neural networks
Linda Albanese, Francesco Alemanno, Andrea Alessandrelli +1
Understanding the glassy nature of neural networks is pivotal both for theoretical and computational advances in Machine Learning and Theoretical Artificial Intelligence. Keeping t…
Rigorous approaches for spin glass and Gaussian spin glass with P-wise interactions
Linda Albanese, Andrea Alessandrelli
Purpose of this paper is to face up to P-spin glass and Gaussian P-spin model, i.e. spin glasses with polynomial interactions of degree P > 2. We consider the replica symmetry and…
Pattern recognition in Deep Boltzmann machines
Elena Agliari, Linda Albanese, Francesco Alemanno +1
We consider a multi-layer Sherrington-Kirkpatrick spin-glass as a model for deep restricted Boltzmann machines and we solve for its quenched free energy, in the thermodynamic limit…
Replica symmetry breaking in neural networks: a few steps toward rigorous results
Elena Agliari, Linda Albanese, Adriano Barra +1
In this paper we adapt the broken replica interpolation technique (developed by Francesco Guerra to deal with the Sherrington-Kirkpatrick model, namely a pairwise mean-field spin-g…