Google
Google Scholar
MS Academic
CiteSeerX
CORE
Semantic ScholarPaolo Cremonesi
Person information
- affiliation: Politecnico di Milano, Italy
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2020
[c102]Gabriele Prato, Federico Sallemi, Paolo Cremonesi, Mario Scriminaci, Stefan Gudmundsson, Silvio Palumbo:
Outfit Completion and Clothes Recommendation. CHI Extended Abstracts 2020: 1-7- [c101]Luca Benedetto, Andrea Cappelli, Roberto Turrin, Paolo Cremonesi:
R2DE: a NLP approach to estimating IRT parameters of newly generated questions. LAK 2020: 412-421 - [i16]Luca Benedetto, Andrea Cappelli, Roberto Turrin, Paolo Cremonesi:
R2DE: a NLP approach to estimating IRT parameters of newly generated questions. CoRR abs/2001.07569 (2020) - [i15]Luca Benedetto, Andrea Cappelli, Roberto Turrin, Paolo Cremonesi:
Introducing a framework to assess newly created questions with Natural Language Processing. CoRR abs/2004.13530 (2020) - [i14]Stefano Cereda, Gianluca Palermo, Paolo Cremonesi, Stefano Doni:
A Collaborative Filtering Approach for the Automatic Tuning of Compiler Optimisations. CoRR abs/2005.04092 (2020)
2010 – 2019
- 2019
- [j22]Yashar Deldjoo
, Maurizio Ferrari Dacrema, Mihai Gabriel Constantin, Hamid Eghbal-zadeh, Stefano Cereda, Markus Schedl, Bogdan Ionescu, Paolo Cremonesi:
Movie genome: alleviating new item cold start in movie recommendation. User Model. User-Adapt. Interact. 29(2): 291-343 (2019) - [c100]Luca Benedetto, Paolo Cremonesi:
Rexy, A Configurable Application for Building Virtual Teaching Assistants. INTERACT (2) 2019: 233-241 - [c99]Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi:
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features. IntRS@RecSys 2019: 72-76 - [c98]Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach:
Are we really making much progress? A worrying analysis of recent neural recommendation approaches. RecSys 2019: 101-109 - [c97]Cesare Bernardis, Maurizio Ferrari Dacrema, Paolo Cremonesi:
Estimating Confidence of Individual User Predictions in Item-based Recommender Systems. UMAP 2019: 149-156 - [c96]Massimo Quadrana, Dietmar Jannach, Paolo Cremonesi:
Tutorial: Sequence-Aware Recommender Systems. WWW (Companion Volume) 2019: 1316 - [i13]Luca Benedetto, Paolo Cremonesi, Manuel Parenti:
A Virtual Teaching Assistant for Personalized Learning. CoRR abs/1902.09289 (2019) - [i12]Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach:
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches. CoRR abs/1907.06902 (2019) - [i11]Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi:
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features. CoRR abs/1908.11055 (2019) - [i10]Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach:
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research. CoRR abs/1911.07698 (2019) - 2018
- [j21]Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach:
Sequence-Aware Recommender Systems. ACM Comput. Surv. 51(4): 66:1-66:36 (2018) - [j20]Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi:
Using visual features based on MPEG-7 and deep learning for movie recommendation. Int. J. Multim. Inf. Retr. 7(4): 207-219 (2018) - [c95]Luca Benedetto, Paolo Cremonesi, Manuel Parenti:
A Virtual Teaching Assistant for Personalized Learning. CIKM Workshops 2018 - [c94]Yashar Deldjoo, Markus Schedl, Paolo Cremonesi, Gabriella Pasi:
Content-Based Multimedia Recommendation Systems: Definition and Application Domains. IIR 2018 - [c93]Yashar Deldjoo, Mihai Gabriel Constantin, Bogdan Ionescu, Markus Schedl, Paolo Cremonesi:
MMTF-14K: a multifaceted movie trailer feature dataset for recommendation and retrieval. MMSys 2018: 450-455 - [c92]Maurizio Ferrari Dacrema, Alberto Gasparin, Paolo Cremonesi:
Deriving Item Features Relevance from Collaborative Domain Knowledge. KaRS@RecSys 2018: 1-4 - [c91]Yashar Deldjoo, Mihai Gabriel Constantin, Hamid Eghbal-Zadeh, Bogdan Ionescu, Markus Schedl, Paolo Cremonesi:
Audio-visual encoding of multimedia content for enhancing movie recommendations. RecSys 2018: 455-459 - [c90]Massimo Quadrana, Paolo Cremonesi:
Sequence-aware recommendation. RecSys 2018: 539-540 - [c89]Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach:
Sequence-aware Recommender Systems. UMAP 2018: 373-374 - [p4]Paolo Cremonesi, Franca Garzotto, Maurizio Ferrari Dacrema:
User Preference Sources: Explicit vs. Implicit Feedback. Collaborative Recommendations 2018: 233-252 - [i9]Paolo Cremonesi, Chiara Francalanci, Alessandro Poli, Roberto Pagano, Luca Mazzoni, Alberto Maggioni, Mehdi Elahi:
Social Network based Short-Term Stock Trading System. CoRR abs/1801.05295 (2018) - [i8]Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach:
Sequence-Aware Recommender Systems. CoRR abs/1802.08452 (2018) - [i7]Cesare Bernardis, Maurizio Ferrari Dacrema, Paolo Cremonesi:
A novel graph-based model for hybrid recommendations in cold-start scenarios. CoRR abs/1808.10664 (2018) - [i6]Maurizio Ferrari Dacrema, Paolo Cremonesi:
Eigenvalue analogy for confidence estimation in item-based recommender systems. CoRR abs/1809.02052 (2018) - [i5]Maurizio Ferrari Dacrema, Alberto Gasparin, Paolo Cremonesi:
Deriving item features relevance from collaborative domain knowledge. CoRR abs/1811.01905 (2018) - 2017
- [j19]Paolo Cremonesi, Mehdi Elahi, Franca Garzotto:
User interface patterns in recommendation-empowered content intensive multimedia applications. Multim. Tools Appl. 76(4): 5275-5309 (2017) - [c88]Yashar Deldjoo, Paolo Cremonesi, Markus Schedl, Massimo Quadrana:
The effect of different video summarization models on the quality of video recommendation based on low-level visual features. CBMI 2017: 20:1-20:6 - [c87]Yashar Deldjoo, Cristina Frà, Massimo Valla, Paolo Cremonesi:
Letting Users Assist What to Watch: An Interactive Query-by-Example Movie Recommendation System. IIR 2017: 63-66 - [c86]Stefano Cereda, Leonardo Cella, Paolo Cremonesi:
Estimate Features Relevance for Groups of Users. IIR 2017: 80-83 - [c85]Leonardo Cella, Romaric Gaudel, Paolo Cremonesi:
Kernalized Collaborative Contextual Bandits. RecSys Posters 2017 - [c84]Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi:
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. RecSys 2017: 130-137 - [c83]Mehdi Elahi, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Leonardo Cella, Stefano Cereda, Paolo Cremonesi:
Exploring the Semantic Gap for Movie Recommendations. RecSys 2017: 326-330 - [c82]Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer, Paolo Cremonesi:
The Importance of Song Context in Music Playlists. RecSys Posters 2017 - [c81]Leonardo Cella, Stefano Cereda, Massimo Quadrana, Paolo Cremonesi:
Deriving Item Features Relevance from Past User Interactions. UMAP 2017: 275-279 - [e2]Paolo Cremonesi, Francesco Ricci, Shlomo Berkovsky, Alexander Tuzhilin:
Proceedings of the Eleventh ACM Conference on Recommender Systems, RecSys 2017, Como, Italy, August 27-31, 2017. ACM 2017, ISBN 978-1-4503-4652-8 [contents] - [i4]Roberto Pagano, Massimo Quadrana, Mehdi Elahi, Paolo Cremonesi:
Toward Active Learning in Cross-domain Recommender Systems. CoRR abs/1701.02021 (2017) - [i3]Yashar Deldjoo, Massimo Quadrana, Mehdi Elahi, Paolo Cremonesi:
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation. CoRR abs/1704.06109 (2017) - [i2]Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi:
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. CoRR abs/1706.04148 (2017) - 2016
- [j18]Giuliano Casale, Andrea Sansottera, Paolo Cremonesi:
Compact Markov-modulated models for multiclass trace fitting. Eur. J. Oper. Res. 255(3): 822-833 (2016) - [j17]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Franca Garzotto, Pietro Piazzolla, Massimo Quadrana:
Content-Based Video Recommendation System Based on Stylistic Visual Features. J. Data Semantics 5(2): 99-113 (2016) - [j16]Paolo Cremonesi, Alan Said, Domonkos Tikk, Michelle X. Zhou:
Introduction to the Special Issue on Recommender System Benchmarking. ACM Trans. Intell. Syst. Technol. 7(3): 38:1-38:4 (2016) - [c80]Paolo Cremonesi, Antonella Di Rienzo, Franca Garzotto, Luigi Oliveto, Pietro Piazzolla:
Smart Lighting for Fashion Store Windows. AVI 2016: 13-20 - [c79]Antonella Di Rienzo, Paolo Tagliaferri, Francesco Arenella, Franca Garzotto, Cristina Frà, Paolo Cremonesi, Massimo Valla:
Bridging Physical Space and Digital Landscape to Drive Retail Innovation. AVI 2016: 356-357 - [c78]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Franca Garzotto, Pietro Piazzolla:
Recommending Movies Based on Mise-en-Scene Design. CHI Extended Abstracts 2016: 1540-1547 - [c77]Paolo Cremonesi, Antonella Di Rienzo, Franca Garzotto, Luigi Oliveto, Pietro Piazzolla:
Dynamic and Interactive Lighting for Fashion Store Windows. CHI Extended Abstracts 2016: 2257-2263 - [c76]Paolo Cremonesi, Franca Garzotto, Marco Gribaudo, Pietro Piazzolla, Mauro Iacono:
vMannequin: A Fashion Store Concept Design Tool. ECMS 2016: 527-533 - [c75]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Farshad Bakhshandegan Moghaddam, Andrea Luigi Edoardo Caielli:
How to Combine Visual Features with Tags to Improve Movie Recommendation Accuracy? EC-Web 2016: 34-45 - [c74]Mattia Brusamento, Roberto Pagano, Martha A. Larson, Paolo Cremonesi:
Explicit Elimination of Similarity Blocking for Session-based Recommendation. RecSys Posters 2016 - [c73]Tommaso Carpi, Marco Edemanti, Ervin Kamberoski, Elena Sacchi, Paolo Cremonesi, Roberto Pagano, Massimo Quadrana:
Multi-stack ensemble for job recommendation. RecSys Challenge 2016: 8:1-8:4 - [c72]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi:
Using Visual Features and Latent Factors for Movie Recommendation. CBRecSys@RecSys 2016: 15-18 - [c71]Tamas Motajcsek, Jean-Yves Le Moine, Martha A. Larson, Daniel Kohlsdorf, Andreas Lommatzsch, Domonkos Tikk, Omar Alonso, Paolo Cremonesi, Andrew Demetriou, Kristaps Dobrajs, Franca Garzotto, Ayse Göker, Frank Hopfgartner, Davide Malagoli, Thuy Ngoc Nguyen, Jasminko Novak, Francesco Ricci, Mario Scriminaci, Marko Tkalcic, Anna Zacchi:
Algorithms Aside: Recommendation As The Lens Of Life. RecSys 2016: 215-219 - [c70]Roberto Pagano, Paolo Cremonesi, Martha A. Larson, Balázs Hidasi, Domonkos Tikk, Alexandros Karatzoglou, Massimo Quadrana:
The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems. RecSys 2016: 249-252 - [i1]Yashar Deldjoo, Shengping Zhang, Bahman Zanj, Paolo Cremonesi, Matteo Matteucci:
Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking? CoRR abs/1608.00168 (2016) - 2015
- [c69]Paolo Cremonesi, Mehdi Elahi, Franca Garzotto:
Interaction Design Patterns in Recommender Systems. CHItaly 2015: 66-73 - [c68]Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi, Franca Garzotto:
Toward Effective Movie Recommendations Based on Mise-en-Scène Film Styles. CHItaly 2015: 162-165 - [c67]Paolo Cremonesi, Franca Garzotto, Matteo Guarnerio, Francesco Gusmeroli, Roberto Pagano:
Decision Making through Polarized Summarization of User Reviews. DMRS 2015: 37-40 - [c66]Mona Naseri, Mehdi Elahi, Paolo Cremonesi:
Investigating the Decision Making Process of Users based on the PoliMovie Dataset. DMRS 2015: 41-44 - [c65]Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi:
Toward Building a Content-Based Video Recommendation System Based on Low-Level Features. EC-Web 2015: 45-56 - [c64]Paolo Cremonesi, Primo Modica, Roberto Pagano, Emanuele Rabosio, Letizia Tanca:
Personalized and Context-Aware TV Program Recommendations Based on Implicit Feedback. EC-Web 2015: 57-68 - [c63]Antonella Di Rienzo, Franca Garzotto, Paolo Cremonesi, Cristina Frà, Massimo Valla:
Towards a smart retail environment. UbiComp/ISWC Adjunct 2015: 779-782 - [c62]Antonella Di Rienzo, Franca Garzotto, Paolo Cremonesi, Cristina Frà, Massimo Valla:
Integrated Interaction with Large and Small Devices. FutureMobileUI@MobiSys 2015: 9-11 - [c61]Roberto Turrin, Massimo Quadrana, Andrea Condorelli, Roberto Pagano, Paolo Cremonesi:
30Music Listening and Playlists Dataset. RecSys Posters 2015 - [c60]Franca Garzotto, Antonella Di Rienzo, Ayse Naciye Çelebi Yilmaz, Luigi Oliveto, Paolo Cremonesi, Cristina Frà, Massimo Valla:
Making Fashion More Trendy through Touchless Interactive Displays Integrated with Mobile Devices. ITS 2015: 429-432 - [r1]Iván Cantador, Ignacio Fernández-Tobías, Shlomo Berkovsky, Paolo Cremonesi:
Cross-Domain Recommender Systems. Recommender Systems Handbook 2015: 919-959 - 2014
- [j15]Paolo Cremonesi, Andrea Sansottera:
Indirect estimation of service demands in the presence of structural changes. Perform. Evaluation 73: 18-40 (2014) - [c59]Paolo Cremonesi, Antonella Di Rienzo, Cristina Frà, Franca Garzotto, Luigi Oliveto, Massimo Valla:
Personalized interaction on large displays: the StreetSmart project approach. AVI 2014: 353-354 - [c58]Paolo Cremonesi, Raffaele Facendola, Franca Garzotto, Matteo Guarnerio, Mattia Natali, Roberto Pagano:
Polarized review summarization as decision making tool. AVI 2014: 355-356 - [c57]Alessandro Bozzon, Lora Aroyo, Paolo Cremonesi:
First International Workshop on User Interfaces for Crowdsourcing and Human Computation. AVI 2014: 398-400 - [c56]Paolo Cremonesi, Massimo Quadrana:
Cross-domain recommendations without overlapping data: myth or reality? RecSys 2014: 297-300 - [c55]Martha A. Larson, Paolo Cremonesi, Alexandros Karatzoglou:
Overview of ACM RecSys CrowdRec 2014 workshop: crowdsourcing and human computation for recommender systems. RecSys 2014: 381-382 - [c54]Panagiotis Adamopoulos, Alejandro Bellogín, Pablo Castells, Paolo Cremonesi, Harald Steck:
REDD 2014 - international workshop on recommender systems evaluation: dimensions and design. RecSys 2014: 393-394 - [c53]Iván Cantador, Paolo Cremonesi:
Tutorial on cross-domain recommender systems. RecSys 2014: 401-402 - [c52]Alan Said, Martha A. Larson, Domonkos Tikk, Paolo Cremonesi, Alexandros Karatzoglou, Frank Hopfgartner, Roberto Turrin, Joost Geurts:
User-Item Reciprocity in Recommender Systems: Incentivizing the Crowd. UMAP Workshops 2014 - [c51]Paolo Cremonesi, Franca Garzotto, Roberto Pagano, Massimo Quadrana:
Recommending without short head. WWW (Companion Volume) 2014: 245-246 - [p3]Alan Said, Domonkos Tikk, Paolo Cremonesi:
Benchmarking - A Methodology for Ensuring the Relative Quality of Recommendation Systems in Software Engineering. Recommendation Systems in Software Engineering 2014: 275-300 - 2013
- [j14]Eugenio Capra, Paolo Cremonesi, Chiara Francalanci, Francesco Merlo, Nicola Parolini:
EnergIT: A Methodology for the Incremental Green Design of Data Centers. IJGC 4(1): 83-111 (2013) - [c50]Andrea Sansottera, Giuliano Casale, Paolo Cremonesi:
Fitting second-order acyclic Marked Markovian Arrival Processes. DSN 2013: 1-12 - [c49]Paolo Cremonesi, Franca Garzotto:
Smoothly Extending e-Tourism Services with Personalized Recommendations: A Case Study. EC-Web 2013: 174-181 - [c48]Paolo Cremonesi, Roberto Pagano, Stefano Pasquali, Roberto Turrin:
TV program detection in tweets. EuroITV 2013: 45-54 - [c47]Paolo Cremonesi, Franca Garzotto, Roberto Turrin:
User-Centric vs. System-Centric Evaluation of Recommender Systems. INTERACT (3) 2013: 334-351 - [c46]Paolo Cremonesi, Franca Garzotto, Massimo Quadrana:
Evaluating top-n recommendations "when the best are gone". RecSys 2013: 339-342 - [c45]Andrea Sansottera, Paolo Cremonesi:
Optimal virtual machine scheduling with anvik. VALUETOOLS 2013: 290-293 - [p2]Borzou Rostami, Paolo Cremonesi, Federico Malucelli:
A Graph Optimization Approach to Item-Based Collaborative Filtering. Recent Advances in Computational Optimization 2013: 15-30 - [e1]Paolo Paolini, Paolo Cremonesi, George Lekakos:
11th European Conference on Interactive TV and Video, EuroITV '13, Como, Italy, June 24-26, 2013. ACM 2013, ISBN 978-1-4503-1951-5 [contents] - 2012
- [j13]Paolo Cremonesi, Andrea Sansottera:
Modeling response times in the Google ROADEF/EURO challenge. SIGMETRICS Perform. Evaluation Rev. 40(3): 80-82 (2012) - [j12]Paolo Cremonesi, Franca Garzotto, Roberto Turrin:
Investigating the Persuasion Potential of Recommender Systems from a Quality Perspective: An Empirical Study. ACM Trans. Interact. Intell. Syst. 2(2): 11:1-11:41 (2012) - [c44]Paolo Cremonesi, Francesco Epifania, Franca Garzotto:
User profiling vs. accuracy in recommender system user experience. AVI 2012: 717-720 - [c43]Francesco Epifania, Paolo Cremonesi:
User-Centered Evaluation of Recommender Systems with Comparison between Short and Long Profile. CISIS 2012: 204-211 - [c42]Federico Malucelli, Paolo Cremonesi, Borzou Rostami:
An Application of Bicriterion Shortest Paths to Collaborative Filtering. FedCSIS 2012: 423-429 - [c41]Paolo Cremonesi, Matteo Picozzi, Maristella Matera:
A comparison of recommender systems for mashup composition. RSSE@ICSE 2012: 54-58 - [c40]Andrea Sansottera, Davide Zoni, Paolo Cremonesi, William Fornaciari:
Consolidation of multi-tier workloads with performance and reliability constraints. HPCS 2012: 74-83 - [c39]Paolo Cremonesi, Andrea Sansottera:
Indirect Estimation of Service Demands in the Presence of Structural Changes. QEST 2012: 249-259 - [c38]Paolo Cremonesi, Antonio Donatacci, Franca Garzotto, Roberto Turrin:
Decision-Making in Recommender Systems: The Role of User's Goals and Bounded Resources. Decisions@RecSys 2012: 1-7 - [c37]Alan Said, Domonkos Tikk, Klara Stumpf, Yue Shi, Martha A. Larson, Paolo Cremonesi:
Recommender Systems Evaluation: A 3D Benchmark. RUE@RecSys 2012: 21-23 - [c36]Paolo Cremonesi, Franca Garzotto, Roberto Turrin:
User effort vs. accuracy in rating-based elicitation. RecSys 2012: 27-34 - 2011
- [j11]Andrea Sansottera, Paolo Cremonesi:
Cooling-aware workload placement with performance constraints. Perform. Evaluation 68(11): 1232-1246 (2011) - [c35]Paolo Cremonesi, Andrea Sansottera, Stefano Gualandi:
On the Cooling-Aware Workload Placement Problem. AI for Data Center Management and Cloud Computing 2011 - [c34]Paolo Cremonesi, Franca Garzotto, Sara Negro, Alessandro Vittorio Papadopoulos, Roberto Turrin:
Comparative evaluation of recommender system quality. CHI Extended Abstracts 2011: 1927-1932 - [c33]Paolo Cremonesi, Andrea Sansottera, Stefano Gualandi:
Optimizing cooling and server power consumption. ICCP 2011: 455-462 - [c32]Paolo Cremonesi, Antonio Tripodi, Roberto Turrin:
Cross-Domain Recommender Systems. ICDM Workshops 2011: 496-503 - [c31]Paolo Cremonesi, Franca Garzotto, Sara Negro, Alessandro Vittorio Papadopoulos, Roberto Turrin:
Looking for "Good" Recommendations: A Comparative Evaluation of Recommender Systems. INTERACT (3) 2011: 152-168 - [p1]Riccardo Bambini, Paolo Cremonesi, Roberto Turrin:
A Recommender System for an IPTV Service Provider: a Real Large-Scale Production Environment. Recommender Systems Handbook 2011: 299-331 - 2010
- [j10]Jonatha Anselmi, Paolo Cremonesi:
A unified framework for the bottleneck analysis of multiclass queueing networks. Perform. Evaluation 67(4): 218-234 (2010) - [c30]Paolo Cremonesi, Kanika Dhyani, Andrea Sansottera:
Service Time Estimation with a Refinement Enhanced Hybrid Clustering Algorithm. ASMTA 2010: 291-305 - [c29]Kanika Dhyani, Stefano Gualandi, Paolo Cremonesi:
A Constraint Programming Approach for the Service Consolidation Problem. CPAIOR 2010: 97-101 - [c28]Paolo Cremonesi, Roberto Turrin:
Controlling Consistency in Top-N Recommender Systems. ICDM Workshops 2010: 919-926 - [c27]Paolo Cremonesi, Yehuda Koren, Roberto Turrin:
Performance of recommender algorithms on top-n recommendation tasks. RecSys 2010: 39-46
2000 – 2009
- 2009
- [j9]Paolo Cremonesi, Roberto Turrin, Vassil N. Alexandrov:
Modeling the Effects of Node Heterogeneity on the Performance of Grid Applications. J. Networks 4(9): 837-854 (2009) - [c26]Elica Campochiaro, Riccardo Casatta, Paolo Cremonesi, Roberto Turrin:
Do Metrics Make Recommender Algorithms?. AINA Workshops 2009: 648-653 - [c25]Paolo Cremonesi, Marco Bertoli:
Predicting SPEC Benchmarks Values for Untested Systems. Int. CMG Conference 2009 - [c24]Paolo Cremonesi, Giuseppe Nardiello:
How to Integrate Load Testing with Capacity Planning. Int. CMG Conference 2009 - [c23]Paolo Cremonesi, Giovanni Versaci:
Estimating Server Power Consumption. Int. CMG Conference 2009 - [c22]Jonatha Anselmi, Paolo Cremonesi, Edoardo Amaldi:
On the Consolidation of Data-Centers with Performance Constraints. QoSA 2009: 163-176 - [c21]Paolo Cremonesi, Roberto Turrin:
Analysis of cold-start recommendations in IPTV systems. RecSys 2009: 233-236 - 2008
- [c20]Jonatha Anselmi, Paolo Cremonesi:
Exact Asymptotic Analysis of Closed BCMP Networks with a Common Bottleneck. ASMTA 2008: 206-220 - [c19]Jonatha Anselmi, Paolo Cremonesi:
Bounding the Performance of BCMP Networks with Load-Dependent Stations. MASCOTS 2008: 171-178 - [c18]