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Federico Tomasi
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2020 – today
- 2024
- [c14]Zhenwen Dai, Federico Tomasi, Sina Ghiassian:
In-context Exploration-Exploitation for Reinforcement Learning. ICLR 2024 - [i6]Zhenwen Dai, Federico Tomasi, Sina Ghiassian:
In-context Exploration-Exploitation for Reinforcement Learning. CoRR abs/2403.06826 (2024) - [i5]Federico Tomasi, Francesco Fabbri, Mounia Lalmas, Zhenwen Dai:
Diffusion Model for Slate Recommendation. CoRR abs/2408.06883 (2024) - 2023
- [c13]Federico Tomasi
, Joseph Cauteruccio
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. KDD 2023: 4948-4957 - [i4]Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai:
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. CoRR abs/2310.09123 (2023) - 2022
- [c12]Federico Tomasi, Mounia Lalmas, Zhenwen Dai:
Efficient inference for dynamic topic modeling with large vocabularies. UAI 2022: 1950-1959 - 2021
- [c11]Antonia Saravanou, Federico Tomasi, Rishabh Mehrotra, Mounia Lalmas:
Multi-Task Learning of Graph-based Inductive Representations of Music Content. ISMIR 2021: 602-609 - [i3]Erik Bodin, Federico Tomasi, Zhenwen Dai:
Making Differentiable Architecture Search less local. CoRR abs/2104.10450 (2021) - 2020
- [c10]Federico Tomasi, Rishabh Mehrotra, Aasish Pappu, Judith Bütepage, Brian Brost, Hugo Galvão, Mounia Lalmas:
Query Understanding for Surfacing Under-served Music Content. CIKM 2020: 2765-2772 - [c9]Federico Tomasi, Veronica Tozzo, Annalisa Barla:
Temporal Pattern Detection in Time-Varying Graphical Models. ICPR 2020: 4481-4488 - [c8]Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas:
Contextual and Sequential User Embeddings for Large-Scale Music Recommendation. RecSys 2020: 53-62 - [c7]Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai:
Stochastic Variational Inference for Dynamic Correlated Topic Models. UAI 2020: 859-868
2010 – 2019
- 2019
- [b1]Federico Tomasi:
Graphical Models for Multivariate Time-Series. University of Genoa, Italy, 2019 - 2018
- [c6]Federico Tomasi, Veronica Tozzo, Saverio Salzo
Latent Variable Time-varying Network Inference. KDD 2018: 2338-2346 - [c5]Vanessa D'Amario, Federico Tomasi, Veronica Tozzo, Gabriele Arnulfo, Annalisa Barla, Lino Nobili:
Multi-task multiple kernel learning reveals relevant frequency bands for critical areas localization in focal epilepsy. MLHC 2018: 348-382 - [c4]Federico Tomasi, Veronica Tozzo, Alessandro Verri, Saverio Salzo:
Forward-Backward Splitting for Time-Varying Graphical Models. PGM 2018: 475-486 - [i2]Federico Tomasi, Veronica Tozzo, Saverio Salzo, Alessandro Verri:
Latent variable time-varying network inference. CoRR abs/1802.03987 (2018) - [i1]Veronica Tozzo, Federico Tomasi, Margherita Squillario, Annalisa Barla:
Group induced graphical lasso allows for discovery of molecular pathways-pathways interactions. CoRR abs/1811.09673 (2018) - 2017
- [c3]Federico Tomasi
Icing: Large-Scale Inference of Immunoglobulin Clonotypes. CIBB 2017: 42-50 - [c2]Samuele Fiorini
Adenine: A HPC-Oriented Tool for Biological Data Exploration. CIBB 2017: 51-59 - 2016
- [c1]Matteo Barbieri, Samuele Fiorini, Federico Tomasi, Annalisa Barla
PALLADIO: A Parallel Framework for Robust Variable Selection in High-Dimensional Data. PyHPC@SC 2016: 19-26
Coauthor Index
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last updated on 2024-09-25 00:44 CEST by the dblp team
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