Proceedings

The LKPY Package for Recommender Systems Experiments [PDF]

Michael D Ekstrand (Boise State University)*

Offline Comparison of Ranking Functions using Randomized Data [PDF]

Aman Agarwal (Google); Xuanhui Wang (Google); Cheng Li (Google)*; Michael Bendersky (Google); Marc Najork (Google)

Multi-Armed Bandits for Recommender Systems : A True Story of Accuracy [PDF]

Nicolas Gutowski (Université d'Angers / Groupe ESEO)*; Tassadit Amghar (Université d'Angers); Olivier Camp (Groupe ESEO); Fabien Chhel (Groupe ESEO)

Using offline metrics and user behavior analysis to combine multiple systems for music recommendation [PDF]

Andres Ferraro (Music Technology Group - Universitat Pompeu Fabra)*; Dmitry Bogdanov (Universitat Pompeu Fabra); Kyumin Choi (Kakao Corp); Xavier Serra (Universitat Pompeu Fabra )

Sequeval: A Framework to Assess and Benchmark Sequence-based Recommender Systems [PDF]

Diego Monti (Politecnico di Torino)*; Enrico Palumbo (Istituto Superiore Mario Boella); Giuseppe Rizzo (ISMB); Maurizio Morisio (Politecnico di Torino)

A Distributed and Accountable Approach to Offline Recommender Systems Evaluation [PDF]

Diego Monti (Politecnico di Torino)*; Giuseppe Rizzo (ISMB); Maurizio Morisio (Politecnico di Torino)

Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerce [PDF]

Ladislav Peška (Charles University, Prague)*; Peter Vojtas (Charles University, Prague)

Towards an Offline Evaluation Strategy for Recommender Systems in Personalized Music Video Television [PDF]

Reza Aditya Permadi (TU Delft)*; Martha Larson (Radboud University); Bouke Huurnink (XITE Networks International)

Characterization of Fair Experiments for Recommender System Evaluation – A Formal Analysis [PDF]

Pablo Castells (Universidad Autónoma de Madrid)*; Rocío Cañamares (Universidad Autónoma de Madrid)

Fair Offline Evaluation Methodologies for Implicit-Feedback Recommender Systems with MNAR Data [PDF]

Olivier Jeunen (University of Antwerp)*; Koen Verstrepen (Froomle); Bart Goethals (Universiteit Antwerpen)

Comparing offline and online evaluation results of recommender systems [PDF]

Tomas Rehorek, Ondrej Biza*, Radek Bartyzal*, Pavel Kordik*, Ivan Povalyev, Ondrej Podstavek (Czech Technical University in Prague, Recombee)

On the Design of Estimators for Off-Policy Evaluation [PDF]

Nikos Vlassis (Netflix)*; Aurelien Bibaut (UC Berkeley); Tony Jebara (Netflix)

From User Experience to Offline Metrics and Back Again: A Research Agenda [PDF]

Joseph Konstan (University of Minnesota)*

A More Comprehensive Offline Evaluation of Active Learning in Recommender Systems [PDF]

Diego Carraro (Insight Centre for Data Analytics)*; Derek Bridge (Insight Centre for Data Analytics)

RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising [PDF]

D. Rohde (Criteo), S. Bonner (Criteo), T. Dunlop (Criteo), F. Vasile (Criteo), A. Karatzoglou (Telefonica Research)

Monte Carlo Estimates of Evaluation Metric Error and Bias [PDF]

Mucun Tian (Boise State University); Michael D Ekstrand (Boise State University)*

On measuring polarization using recommender system scores [PDF]

Robert Keyes (Shopify Inc.); Trish Gillett (Shopify Inc.); Putra Manggala (Shopify Inc.)*

CounterFactual Regression with Importance Sampling Weights [PDF]

Negar Hassanpour (University of Alberta)*; Russell Greiner (U Alberta)

BEARS: Towards an Evaluation Framework for Bandit-based Interactive Recommender Systems [PDF]

Andrea P Barraza (Insight Centre for Data Analytics)*