89 citations · 160 across the 4 of their papers we have counts for
8 papers
Electricity Demand Forecasting by Multi-Task Learning
Jean-Baptiste Fiot, Francesco Dinuzzo
We explore the application of kernel-based multi-task learning techniques to forecast the demand of electricity in multiple nodes of a distribution network. We show that recently d…
Learning Output Kernels for Multi-Task Problems
Francesco Dinuzzo
Simultaneously solving multiple related learning tasks is beneficial under a variety of circumstances, but the prior knowledge necessary to correctly model task relationships is ra…
The representer theorem for Hilbert spaces: a necessary and sufficient condition
Francesco Dinuzzo, Bernhard Schölkopf
A family of regularization functionals is said to admit a linear representer theorem if every member of the family admits minimizers that lie in a fixed finite dimensional subspace…
Kernels for linear time invariant system identification
Francesco Dinuzzo
In this paper, we study the problem of identifying the impulse response of a linear time invariant (LTI) dynamical system from the knowledge of the input signal and a finite set of…
Learning from Distributions via Support Measure Machines
Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo +1
This paper presents a kernel-based discriminative learning framework on probability measures. Rather than relying on large collections of vectorial training examples, our framework…
Fixed-point and coordinate descent algorithms for regularized kernel methods
Francesco Dinuzzo
In this paper, we study two general classes of optimization algorithms for kernel methods with convex loss function and quadratic norm regularization, and analyze their convergence…