Publications associées à Filtrage collaboratif

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

Rachid Guerraoui, Sadegh Farhadkhani, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

We study Byzantine collaborative learning, where n nodes seek to collectively learn from each others' local data. The data distribution may vary from one node to another. No node is trusted, and f < n nodes can behave arbitrarily. We prove that collaborati ...

2021

The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Diversity-aware platform design is a paradigm that responds to the ethical challenges of existing social media platforms. Available platforms have been criticized for minimizing users' autonomy, marginalizing minorities, and exploiting users' data for prof ...

ASSOC COMPUTING MACHINERY2021

Drift Estimation of Multiscale Diffusions Based on Filtered Data

Assyr Abdulle, Giacomo Garegnani, Andrea Zanoni, Grigorios A. Pavliotis

We study the problem of drift estimation for two-scale continuous time series. We set ourselves in the framework of overdamped Langevin equations, for which a single-scale surrogate homogenized equation exists. In this setting, estimating the drift coeffic ...

2021

Advances in Bias-aware Recommendation on the Web

Mirko Marras

The goal of this tutorial is to provide the WSDM community with recent advances on the assessment and mitigation of data and algorithmic bias in recommender systems. We first introduce conceptual foundations, by presenting the state of the art and describi ...

ASSOC COMPUTING MACHINERY2021

The Winner Takes it All: Geographic Imbalance and Provider (Un)fairness in Educational Recommender Systems

Mirko Marras

Educational recommender systems channel most of the research efforts on the effectiveness of the recommended items. While teachers have a central role in online platforms, the impact of recommender systems for teachers in terms of the exposure such systems ...

ASSOC COMPUTING MACHINERY2021

Detecting 32 Pedestrian Attributes for Autonomous Vehicles

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

Pedestrians are arguably one of the most safety-critical road users to consider for autonomous vehicles in urban areas. In this paper, we address the problem of jointly detecting pedestrians and recognizing 32 pedestrian attributes from a single image. The ...

2021

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

Boi Faltings, Diego Matteo Antognini

Today, recommender systems are an inevitable part of everyone's daily digital routine and are present on most internet platforms. State-of-the-art deep learning-based models require a large number of data to achieve their best performance. Many datasets fu ...

EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA2020

Modurec: Recommender Systems with Feature and Time Modulation

Pascal Frossard, Clément Arthur Yvon Vignac, Javier Alejandro Maroto Morales

Current state of the art algorithms for recommender systems are mainly based on collaborative filtering, which exploits user ratings to discover latent factors in the data. These algorithms unfortunately do not make effective use of other features, which c ...

2020

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Filtrage collaboratif

Studying Alignment in Spontaneous Speech via Automatic Methods: How Do Children Use Task-specific Referents to Succeed in a Collaborative Learning Activity?

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations

Interplay between upsampling and regularization for provider fairness in recommender systems

Drift Estimation of Multiscale Diffusions Based on Filtered Data

Advances in Bias-aware Recommendation on the Web

The Winner Takes it All: Geographic Imbalance and Provider (Un)fairness in Educational Recommender Systems

Detecting 32 Pedestrian Attributes for Autonomous Vehicles

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

Modurec: Recommender Systems with Feature and Time Modulation

Graph Chatbot

Chattez avec Graph Search

The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

Modurec: Recommender Systems with Feature and Time Modulation

Interplay between upsampling and regularization for provider fairness in recommender systems

Drift Estimation of Multiscale Diffusions Based on Filtered Data

The Winner Takes it All: Geographic Imbalance and Provider (Un)fairness in Educational Recommender Systems

Advances in Bias-aware Recommendation on the Web

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

Detecting 32 Pedestrian Attributes for Autonomous Vehicles

Studying Alignment in Spontaneous Speech via Automatic Methods: How Do Children Use Task-specific Referents to Succeed in a Collaborative Learning Activity?