Djallel Bouneffouf

research

∙ 06/12/2023

Interpolating Item and User Fairness in Recommendation Systems

Online platforms employ recommendation systems to enhance customer engag...

0 Qinyi Chen, et al. ∙

research

∙ 06/06/2023

Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosis

In response to the global challenge of mental health problems, we propos...

3 Yeldar Toleubay, et al. ∙

research

∙ 04/02/2023

Towards Healthy AI: Large Language Models Need Therapists Too

Recent advances in large language models (LLMs) have led to the developm...

8 Baihan Lin, et al. ∙

research

∙ 03/16/2023

Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics

We introduce a Reinforcement Learning Psychotherapy AI Companion that ge...

12 Baihan Lin, et al. ∙

research

∙ 02/21/2023

TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts

We present the TherapyView, a demonstration system to help therapists vi...

5 Baihan Lin, et al. ∙

research

∙ 02/02/2023

A Survey on Compositional Generalization in Applications

The field of compositional generalization is currently experiencing a re...

7 Baihan Lin, et al. ∙

research

∙ 10/28/2022

Dynamic Bandits with an Auto-Regressive Temporal Structure

Multi-armed bandit (MAB) problems are mainly studied under two extreme s...

0 Qinyi Chen, et al. ∙

research

∙ 10/27/2022

Working Alliance Transformer for Psychotherapy Dialogue Classification

As a predictive measure of the treatment outcome in psychotherapy, the w...

5 Baihan Lin, et al. ∙

research

∙ 09/08/2022

Survey on Applications of Neurosymbolic Artificial Intelligence

In recent years, the Neurosymbolic framework has attracted a lot of atte...

0 Djallel Bouneffouf, et al. ∙

research

∙ 08/22/2022

Targeted Advertising on Social Networks Using Online Variational Tensor Regression

This paper is concerned with online targeted advertising on social netwo...

0 Tsuyoshi Idé, et al. ∙

research

∙ 04/13/2022

Neural Topic Modeling of Psychotherapy Sessions

In this work, we compare different neural topic modeling methods in lear...

11 Baihan Lin, et al. ∙

research

∙ 04/12/2022

Deep Annotation of Therapeutic Working Alliance in Psychotherapy

The therapeutic working alliance is an important predictor of the outcom...

1 Baihan Lin, et al. ∙

research

∙ 06/30/2021

Optimal Epidemic Control as a Contextual Combinatorial Bandit with Budget

In light of the COVID-19 pandemic, it is an open challenge and critical ...

17 Baihan Lin, et al. ∙

research

∙ 03/15/2021

Reinforcement Learning with Algorithms from Probabilistic Structure Estimation

Reinforcement learning (RL) algorithms aim to learn optimal decisions in...

0 Jonathan P. Epperlein, et al. ∙

research

∙ 01/04/2021

Etat de l'art sur l'application des bandits multi-bras

The Multi-armed bandit offer the advantage to learn and exploit the alre...

0 Djallel Bouneffouf, et al. ∙

research

∙ 10/22/2020

Predicting Human Decision Making in Psychological Tasks with Recurrent Neural Networks

Unlike traditional time series, the action sequences of human decision m...

15 Baihan Lin, et al. ∙

research

∙ 10/15/2020

Double-Linear Thompson Sampling for Context-Attentive Bandits

In this paper, we analyze and extend an online learning framework known ...

0 Djallel Bouneffouf, et al. ∙

research

∙ 09/29/2020

Learned Fine-Tuner for Incongruous Few-Shot Learning

Model-agnostic meta-learning (MAML) effectively meta-learns an initializ...

0 Pu Zhao, et al. ∙

research

∙ 07/21/2020

Spectral Clustering using Eigenspectrum Shape Based Nystrom Sampling

Spectral clustering has shown a superior performance in analyzing the cl...

0 Djallel Bouneffouf, et al. ∙

research

∙ 07/17/2020

Computing the Dirichlet-Multinomial Log-Likelihood Function

Dirichlet-multinomial (DMN) distribution is commonly used to model over-...

0 Djallel Bouneffouf, et al. ∙

research

∙ 07/13/2020

Contextual Bandit with Missing Rewards

We consider a novel variant of the contextual bandit problem (i.e., the ...

0 Djallel Bouneffouf, et al. ∙

research

∙ 06/26/2020

Online learning with Corrupted context: Corrupted Contextual Bandits

We consider a novel variant of the contextual bandit problem (i.e., the ...

0 Djallel Bouneffouf, et al. ∙

research

∙ 06/17/2020

Solving Constrained CASH Problems with ADMM

The CASH problem has been widely studied in the context of automated con...

0 Parikshit Ram, et al. ∙

research

∙ 06/09/2020

Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior

Prisoner's Dilemma mainly treat the choice to cooperate or defect as an ...

1 Baihan Lin, et al. ∙

research

∙ 05/10/2020

Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL

Artificial behavioral agents are often evaluated based on their consiste...

2 Baihan Lin, et al. ∙

research

∙ 05/04/2020

Hyper-parameter Tuning for the Contextual Bandit

We study here the problem of learning the exploration exploitation trade...

0 Djallel Bouneffouf, et al. ∙

research

∙ 10/22/2019

How can AI Automate End-to-End Data Science?

Data science is labor-intensive and human experts are scarce but heavily...

0 Charu Aggarwal, et al. ∙

research

∙ 06/21/2019

Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders

Drawing an inspiration from behavioral studies of human decision making,...

0 Baihan Lin, et al. ∙

research

∙ 06/21/2019

Split Q Learning: Reinforcement Learning with Two-Stream Rewards

Drawing an inspiration from behavioral studies of human decision making,...

0 Baihan Lin, et al. ∙

research

∙ 05/01/2019

Automated Machine Learning via ADMM

We study the automated machine learning (AutoML) problem of jointly sele...

0 Sijia Liu, et al. ∙

research

∙ 09/21/2018

Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration

Autonomous cyber-physical agents and systems play an increasingly large ...

16 Ritesh Noothigattu, et al. ∙

research

∙ 09/15/2018

Incorporating Behavioral Constraints in Online AI Systems

AI systems that learn through reward feedback about the actions they tak...

0 Avinash Balakrishnan, et al. ∙

research

∙ 06/24/2018

Beyond Backprop: Alternating Minimization with co-Activation Memory

We propose a novel online algorithm for training deep feedforward neural...

0 Anna Choromanska, et al. ∙

research

∙ 02/03/2018

Adaptive Representation Selection in Contextual Bandit with Unlabeled History

We consider an extension of the contextual bandit setting, motivated by ...

0 Baihan Lin, et al. ∙

research

∙ 11/17/2017

Scalable Recollections for Continual Lifelong Learning

Given the recent success of Deep Learning applied to a variety of single...

0 Matthew Riemer, et al. ∙

research

∙ 06/07/2017

Bandit Models of Human Behavior: Reward Processing in Mental Disorders

Drawing an inspiration from behavioral studies of human decision making,...

0 Djallel Bouneffouf, et al. ∙

research

∙ 05/10/2017

Context Attentive Bandits: Contextual Bandit with Restricted Context

We consider a novel formulation of the multi-armed bandit model, which w...

0 Djallel Bouneffouf, et al. ∙

research

∙ 08/10/2014

Exponentiated Gradient Exploration for Active Learning

Active learning strategies respond to the costly labelling task in a sup...

0 Djallel Bouneffouf, et al. ∙

research

∙ 02/09/2014

Recommandation mobile, sensible au contexte de contenus évolutifs: Contextuel-E-Greedy

We introduce in this paper an algorithm named Contextuel-E-Greedy that t...

0 Djallel Bouneffouf, et al. ∙

research

∙ 05/10/2013

Exponentiated Gradient LINUCB for Contextual Multi-Armed Bandits

We present Exponentiated Gradient LINUCB, an algorithm for con-textual m...

0 Djallel Bouneffouf, et al. ∙

research

∙ 01/18/2013

Applying machine learning techniques to improve user acceptance on ubiquitous environement

Ubiquitous information access becomes more and more important nowadays a...

0 Djallel Bouneffouf, et al. ∙

Djallel Bouneffouf

Featured Co-authors