Publications associées à Marché en ligne

Dynamic Vehicle Drifting With Nonlinear MPC and a Fused Kinematic-Dynamic Bicycle Model

In this letter we present a versatile trajectory optimization framework that leverages a fused kinematic-dynamic bicycle model for highly dynamic vehicle drifting maneuvers. Our framework can be used online to generate drifting maneuvers, offline to plan d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Context-Tree Recommendation vs Matrix-Factorization: Algorithm Selection and Live Users Evaluation

Boi Faltings, Vincent Jean Fabrice Schickel, Stéphane Bernard Martin

We describe the selection, implementation and online evaluation of two e-commerce recommender systems developed with our partner company, Prediggo. The first one is based on the novel method of Bayesian Variable-order Markov Modeling (BVMM). The second, SS ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2019

Privacy in Recommender Systems

Mahsa Taziki

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. Recommenders are machine learning approach and are becoming one of the main ways to navigate the Internet. They recommend appropria ...

EPFL2018

Coalitional Control for Self-Organizing Agents

Ezequiel González Debada

Coalitional control is concerned with the management of multi-agent systems where cooperation cannot be taken for granted (due to, e.g., market competition, logistics). This paper proposes a model predictive control (MPC) framework aimed at large-scale dyn ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

When Sheep Shop: Measuring Herding Effects in Product Ratings with Natural Experiments

Robert West, Gael Lederrey

As online shopping becomes ever more prevalent, customers rely increasingly on product rating websites for making purchase decisions. The reliability of online ratings, however, is potentially compromised by the so-called herding effect: when rating a prod ...

2018

D2P: Distance-Based Differential Privacy in Recommenders

Rachid Guerraoui, Anne-Marie Kermarrec, Mahsa Taziki, Rhicheek Patra

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. This information growth calls for recommenders that personalize the in- formation proposed to each individual user. Nevertheless, p ...

Assoc Computing Machinery2015

Coopetition within and between value networks – a typology and a modelling framework

Alain Wegmann, Arash Golnam

This study develops a typology of coopetition in value networks, wherein a distinction is made based on two factors. Firstly, whether coopetition takes place inside a particular value network (i.e., intra-value network coopetition) or between value network ...

2014

Coopetition-based business models: The case of Amazon.com

Alain Wegmann, Arash Golnam

Coopetition (collaboration between competing firms) is a phenomenon that has recently captured a great deal of attention due to its increasing relevance to business practice. However, current research on coopetition is still short on explaining how the pot ...

2014

Trust-aware Privacy Control for Social Media

Denis Gillet, Na Li, Maryam Najafian-Razavi

Due to the huge exposure of personal information in social media, a challenge now is to design effective privacy mechanisms that protect against unauthorized access to social data. In this paper, a trust model for social media is first presented. Based on ...

2011

Coopetition In The Global Book Industry: The Case Of Amazon.Com’s Evolution

Alain Wegmann, Arash Golnam

Coopetition (collaboration between competing firms) is a phenomenon which has recently captured a great deal of attention due to its increasing relevance to business practice. The current research on coopetition is still short in explaining how the potenti ...

2011