1 citations · 2 across the 4 of their papers we have counts for
5 papers
Finite convergence and minimizer extraction in moment relaxations with correlative sparsity
Giovanni Fantuzzi, Federico Fuentes
We identify a new sufficient condition for the finite convergence of moment relaxations of polynomial optimization problems with correlative sparsity. This condition, which follows…
Exact Sequence Interpolation with Transformers
Albert Alcalde, Giovanni Fantuzzi, Enrique Zuazua
We prove that transformers can exactly interpolate datasets of finite input sequences in , , with corresponding output sequences of smaller or equal length.…
Clustering in pure-attention hardmax transformers and its role in sentiment analysis
Albert Alcalde, Giovanni Fantuzzi, Enrique Zuazua
Transformers are extremely successful machine learning models whose mathematical properties remain poorly understood. Here, we rigorously characterize the behavior of transformers…
Data-driven discovery of polynomial ODEs with provably bounded solutions
Albert Alcalde, Giovanni Fantuzzi
We introduce SILAS, a data-driven framework for discovering polynomial ordinary differential equations (ODEs) with provably bounded trajectories. Boundedness is certified by compac…
Moment-SOS hierarchies for arrow-type polynomial matrix inequalities with applications to structural optimization
Marouan Handa, Marek Tyburec, Giovanni Fantuzzi +2
The Arrow Decomposition (AD) technique, initially introduced in [Mathematical Programming 190(1-2) (2021), pp 105-134], demonstrated superior scalability over the classical chordal…