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Interplay between upsampling and regularization for provider fairness in recommender systems

Related publications (32)

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Distributed user profiling via spectral methods

Dan-Cristian Tomozei

User profiling is a useful primitive for constructing personalised services, such as content recommendation. In the present paper we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local informatio ...

2014

Enhancing statistical performance of data-driven controller tuning via L2-regularization

Alireza Karimi

Noniterative data-driven techniques are design methods that allow optimal feedback control laws to be derived from input-output (I/O) data only, without the need of a model of the process. A drawback of these methods is that, in their standard formulation, ...

Pergamon-Elsevier Science Ltd2014

Widgets and Spaces

Evgeny Bogdanov

Social media platforms are created and exploited for various activities carried out individually or collaboratively and relying on different resources and tools. Social media platforms are inherently contextual; the context being defined as a specific acti ...

EPFL2013

Recommendation using textual opinions

Boi Faltings, Claudiu-Cristian Musat

Many web sites collect reviews of products and services and use them provide rankings of their quality. However, such rankings are not personalized. We investigate how the information in the reviews written by a particular user can be used to personalize t ...

2013

CoFeed: privacy-preserving Web search recommendation based on collaborative aggregation of interest feedback

Martin Rajman, Vinh Toan Luu, Pascal Felber

Search engines essentially rely on the structure of the graph of hyperlinks. Although accurate for the main trend, this is not effective when some query is ambiguous. Leveraging semantic information by the mean of interest matching allows proposing complem ...

Wiley-Blackwell2013

TripEneer: User-based Travel Plan Recommendation Application

Karl Aberer, Surender Reddy Yerva, Flavia Adelina Grosan, Alexandru Octavian Tandrau

Current travel recommendation systems are helpful in addressing a traveler's information needs to certain extent, however, most of them fail to factor in the user in their recommendations. TripEneer proposes travel recommendations to a traveler by keeping ...

2013

Design and User Perception Issues for Personality-Engaged Recommender Systems

Rong Hu

Recommender systems have emerged, as an intelligent information filtering tool, to help users effectively identify information items of interest from a set of overwhelming choices and provide personalized services. Most recommendation technologies typicall ...

EPFL2012

Critiquing-based recommenders: survey and emerging trends

Pearl Pu Faltings, Li Chen

Critiquing-based recommender systems elicit users' feedback, called critiques, which they made on the recommended items. This conversational style of interaction is in contract to the standard model where users receive recommendations in a single interacti ...

2012

Predicting behavior of Twitter Users

Adela Maznikar

Social networks today are great source of data which can be used and analyzed in different ways. In our project the main goal is to predict the behavior of the users, more accurately said: we try to predict what will a particular user tweet in the future, ...

2011

Modeling methodology of high-voltage substrate minority and majority carrier injections

Maher Kayal, Jean-Michel Sallese, Fabrizio Lo Conte

This paper presents a modeling methodology for substrate current coupling mechanisms. An enhanced model of the diode ensuring continuity of minority carriers is used to build an equivalent schematic, accounting for minority and majority carrier propagation ...

2010