477 citations · 1.4k across the 57 of their papers we have counts for
5 papers · 1 filter
Bidirectional deep-readout echo state networks
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse +1
We propose a deep architecture for the classification of multivariate time series. By means of a recurrent and untrained reservoir we generate a vectorial representation that embed…
Kafnets: kernel-based non-parametric activation functions for neural networks
Simone Scardapane, Steven Van Vaerenbergh, Simone Totaro +1
Neural networks are generally built by interleaving (adaptable) linear layers with (fixed) nonlinear activation functions. To increase their flexibility, several authors have propo…
Stochastic Training of Neural Networks via Successive Convex Approximations
Simone Scardapane, Paolo Di Lorenzo
This paper proposes a new family of algorithms for training neural networks (NNs). These are based on recent developments in the field of non-convex optimization, going under the g…
Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure
Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaria
In kernel methods, temporal information on the data is commonly included by using time-delayed embeddings as inputs. Recently, an alternative formulation was proposed by defining a…
Adaptation and learning over networks for nonlinear system modeling
Simone Scardapane, Jie Chen, Cédric Richard
In this chapter, we analyze nonlinear filtering problems in distributed environments, e.g., sensor networks or peer-to-peer protocols. In these scenarios, the agents in the environ…