research
∙
06/12/2023
Interpolating Item and User Fairness in Recommendation Systems
Online platforms employ recommendation systems to enhance customer engag...
share
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...
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...
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...
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...
research
∙
02/02/2023
A Survey on Compositional Generalization in Applications
The field of compositional generalization is currently experiencing a re...
research
∙
10/28/2022
Dynamic Bandits with an Auto-Regressive Temporal Structure
Multi-armed bandit (MAB) problems are mainly studied under two extreme s...
research
∙
10/27/2022
Working Alliance Transformer for Psychotherapy Dialogue Classification
As a predictive measure of the treatment outcome in psychotherapy, the w...
research
∙
09/08/2022
Survey on Applications of Neurosymbolic Artificial Intelligence
In recent years, the Neurosymbolic framework has attracted a lot of atte...
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...
research
∙
04/13/2022
Neural Topic Modeling of Psychotherapy Sessions
In this work, we compare different neural topic modeling methods in lear...
research
∙
04/12/2022
Deep Annotation of Therapeutic Working Alliance in Psychotherapy
The therapeutic working alliance is an important predictor of the outcom...
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 ...
research
∙
03/15/2021
Reinforcement Learning with Algorithms from Probabilistic Structure Estimation
Reinforcement learning (RL) algorithms aim to learn optimal decisions in...
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...
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...
research
∙
10/15/2020
Double-Linear Thompson Sampling for Context-Attentive Bandits
In this paper, we analyze and extend an online learning framework known ...
research
∙
09/29/2020
Learned Fine-Tuner for Incongruous Few-Shot Learning
Model-agnostic meta-learning (MAML) effectively meta-learns an initializ...
research
∙
07/21/2020
Spectral Clustering using Eigenspectrum Shape Based Nystrom Sampling
Spectral clustering has shown a superior performance in analyzing the cl...
research
∙
07/17/2020
Computing the Dirichlet-Multinomial Log-Likelihood Function
Dirichlet-multinomial (DMN) distribution is commonly used to model over-...
research
∙
07/13/2020
Contextual Bandit with Missing Rewards
We consider a novel variant of the contextual bandit problem (i.e., the ...
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 ...
research
∙
06/17/2020
Solving Constrained CASH Problems with ADMM
The CASH problem has been widely studied in the context of automated con...
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 ...
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...
research
∙
05/04/2020
Hyper-parameter Tuning for the Contextual Bandit
We study here the problem of learning the exploration exploitation trade...
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...
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,...
research
∙
06/21/2019
Split Q Learning: Reinforcement Learning with Two-Stream Rewards
Drawing an inspiration from behavioral studies of human decision making,...
research
∙
05/01/2019
Automated Machine Learning via ADMM
We study the automated machine learning (AutoML) problem of jointly sele...
research
∙
09/21/2018
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration
Autonomous cyber-physical agents and systems play an increasingly large ...
research
∙
09/15/2018
Incorporating Behavioral Constraints in Online AI Systems
AI systems that learn through reward feedback about the actions they tak...
research
∙
06/24/2018
Beyond Backprop: Alternating Minimization with co-Activation Memory
We propose a novel online algorithm for training deep feedforward neural...
research
∙
02/03/2018
Adaptive Representation Selection in Contextual Bandit with Unlabeled History
We consider an extension of the contextual bandit setting, motivated by ...
research
∙
11/17/2017
Scalable Recollections for Continual Lifelong Learning
Given the recent success of Deep Learning applied to a variety of single...
research
∙
06/07/2017
Bandit Models of Human Behavior: Reward Processing in Mental Disorders
Drawing an inspiration from behavioral studies of human decision making,...
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...
research
∙
08/10/2014
Exponentiated Gradient Exploration for Active Learning
Active learning strategies respond to the costly labelling task in a sup...
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...
research
∙
05/10/2013
Exponentiated Gradient LINUCB for Contextual Multi-Armed Bandits
We present Exponentiated Gradient LINUCB, an algorithm for con-textual m...
research
∙
01/18/2013
