Djallel Bouneffouf

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Finite-time analysis of the multi-armed bandit problem with known trend

Djallel Bouneffouf
2016 IEEE Congress on Evolutionary Computation…
2016

We study here an a problem called “the multi-armed bandit problem with known trend”, where an agent knows the shape of the reward function of each arm but not its distribution. This problem is… (More)

Hybrid-ε-greedy for Mobile Context-Aware Recommender System

Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Gançarski
PAKDD
2012

The wide development of mobile applications provides a considerable amount of data of all types. In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information… (More)

A Contextual-Bandit Algorithm for Mobile Context-Aware Recommender System

Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Gançarski
ICONIP
2012

Most existing approaches in Mobile Context-Aware Recommender Systems focus on recommending relevant items to users taking into account contextual information, such as time, location, or social… (More)

Contextual Bandit for Active Learning: Active Thompson Sampling

Djallel Bouneffouf, Romain Laroche, Tanguy Urvoy, Raphaël Féraud, Robin Allesiardo
ICONIP
2014

The labelling of training examples is a costly task in a supervised classification. Active learning strategies answer this problem by selecting the most useful unlabelled examples to train a… (More)

DRARS, A Dynamic Risk-Aware Recommender System

Djallel Bouneffouf
2013

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and… (More)

Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering

The Nyström sampling provides an efficient approach for large scale clustering problems, by generating a low-rank matrix approximation. However, existing sampling methods are limited by their… (More)

Following the User's Interests in Mobile Context-Aware Recommender Systems: The Hybrid-e-greedy Algorithm

Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Gançarski
2012 26th International Conference on Advanced…
2012

The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS)… (More)

A Neural Networks Committee for the Contextual Bandit Problem

Robin Allesiardo, Raphaël Féraud, Djallel Bouneffouf
ICONIP
2014

This paper presents a new contextual bandit algorithm, NeuralBandit, which does not need hypothesis on stationarity of contexts and rewards. Several neural networks are trained to modelize the value… (More)

Ensemble Minimum Sum of Squared Similarities sampling for Nyström-based spectral clustering

Djallel Bouneffouf, Inanç Birol
2016 International Joint Conference on Neural…
2016

Spectral clustering is a powerful approach for clustering, with applications across multiple disciplines, including bioinformatics. However, the way its computational complexity scales limits its… (More)

Multi-armed Bandit Problem with Known Trend

We consider a variant of the multi-armed bandit model, which we call multi-armed bandit problem with known trend, where the gambler knows the shape of the reward function of each arm but not its… (More)

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