Search Results for author: Federico Tomasi

Found 5 papers, 1 papers with code

In-context Exploration-Exploitation for Reinforcement Learning

no code implementations11 Mar 2024 Zhenwen Dai, Federico Tomasi, Sina Ghiassian

In-context learning is a promising approach for online policy learning of offline reinforcement learning (RL) methods, which can be achieved at inference time without gradient optimization.

Bayesian Inference Bayesian Optimization +3

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning

no code implementations13 Oct 2023 Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai

In this paper, we present a reinforcement learning framework that solves for such limitations by directly optimizing for user satisfaction metrics via the use of a simulated playlist-generation environment.

Collaborative Filtering reinforcement-learning

Making Differentiable Architecture Search less local

no code implementations21 Apr 2021 Erik Bodin, Federico Tomasi, Zhenwen Dai

Neural architecture search (NAS) is a recent methodology for automating the design of neural network architectures.

Neural Architecture Search

Group induced graphical lasso allows for discovery of molecular pathways-pathways interactions

no code implementations21 Nov 2018 Veronica Tozzo, Federico Tomasi, Margherita Squillario, Annalisa Barla

In this context, high-level layers may considered as groups of variables interacting in lower-level layers.

Latent Variable Time-varying Network Inference

1 code implementation12 Feb 2018 Federico Tomasi, Veronica Tozzo, Saverio Salzo, Alessandro Verri

The estimation of the contribution of the latent factors is embedded in the model which produces both sparse and low-rank components for each time point.

Sociology Time Series +1

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