FERRARI DACREMA, MAURIZIO

FERRARI DACREMA, MAURIZIO  

DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIA  

Dacrema M.F.; Ferrari Dacrema, Maurizio; Dacrema, Maurizio Ferrari  

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Titolo Data di pubblicazione Autori File
Aggregating models for anomaly detection in space systems: Results from the FCTMAS study 1-gen-2019 Amigoni, FrancescoFERRARI DACREMA, MAURIZIOLavagna, Michèle +
Are we really making much progress? A worrying analysis of recent neural recommendation approaches 1-gen-2019 Dacrema, Maurizio FerrariCremonesi, Paolo +
Artist-driven layering and user's behaviour impact on recommendations in a playlist continuation scenario 1-gen-2018 ANTENUCCI, SEBASTIANOCHIOSO, EMANUELEDERVISHAJ, ERVINKANG, SHUWENSCARLATTI, TOMMASOFerrari Dacrema Maurizio. +
ContentWise Impressions: An Industrial Dataset with Impressions Included 1-gen-2020 Perez Maurera F. B.Ferrari Dacrema M.Cremonesi P. +
Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems 1-gen-2020 Ferrari Dacrema M.Cremonesi P. +
Demonstrating the Equivalence of List Based and Aggregate Metrics to Measure the Diversity of Recommendations (Student Abstract) 1-gen-2021 maurizio ferrari dacrema
Deriving item features relevance from collaborative domain knowledge 1-gen-2018 Ferrari Dacrema M.Gasparin A.Cremonesi P.
Design and Evaluation of Cross-Domain Recommender Systems 1-gen-2022 Dacrema, Maurizio FerrariCremonesi, Paolo +
Eigenvalue analogy for confidence estimation in item-based recommender systems 1-gen-2018 M. Ferrari DacremaP. Cremonesi
Estimating confidence of individual user predictions in item-based recommender systems 1-gen-2019 Bernardis C.Ferrari Dacrema M.Cremonesi P.
Evaluating the job shop scheduling problem on a D-wave quantum annealer 1-gen-2022 Carugno, CostantinoFerrari Dacrema, MaurizioCremonesi, Paolo
An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering 1-gen-2022 Pérez Maurera, Fernando BenjamínFerrari Dacrema, MaurizioCremonesi, Paolo
Feature selection for recommender systems with quantum computing 1-gen-2021 Nembrini R.Ferrari Dacrema M.Cremonesi P.
From Data Analysis to Intent-based Recommendation: an Industrial Case Study in the Video Domain 1-gen-2022 Bernardis CesareDacrema Maurizio FerrariMaurera Peréz Fernando BenjaminQuadrana MassimoCremonesi Paolo +
Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank 1-gen-2019 Bernardis C.Ferrari Dacrema M. +
Lightweight and Scalable Model for Tweet Engagements Predictions in a Resource-constrained Environment 1-gen-2021 Carminati, LucaLodigiani, GiacomoMaldini, PietroMeta, SamueleMetaj, StivenPisa, ArcangeloSanvito, AlessandroSurricchio, MattiaPérez Maurera, Fernando BenjamínBernardis, CesareFerrari Dacrema, Maurizio
Measuring the ranking quality of recommendations in a two-dimensional carousel setting 1-gen-2021 Felicioni N.Ferrari Dacrema M.Perez Maurera F. B.Cremonesi P.
Measuring the User Satisfaction in a Recommendation Interface with Multiple Carousels 1-gen-2021 Felicioni N.Ferrari Dacrema M.Cremonesi P.
Methodological Issues in Recommender Systems Research (Extended Abstract) 1-gen-2020 Ferrari Dacrema M.Cremonesi P. +
A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels 1-gen-2021 Felicioni N.Ferrari Dacrema M.Cremonesi P.