Heriberto Cuayáhuitl | DeepAI

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∙ 08/24/2023

Sparks of Large Audio Models: A Survey and Outlook

This survey paper provides a comprehensive overview of the recent advanc...

0 Siddique Latif, et al. ∙

∙ 03/21/2023

Transformers in Speech Processing: A Survey

The remarkable success of transformers in the field of natural language ...

1 Siddique Latif, et al. ∙

∙ 07/31/2022

Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination

Learning robotic tasks in the real world is still highly challenging and...

1 Abdalkarim Mohtasib, et al. ∙

∙ 12/10/2021

Reward-Based Environment States for Robot Manipulation Policy Learning

Training robot manipulation policies is a challenging and open problem i...

0 Cédérick Mouliets, et al. ∙

∙ 08/06/2021

A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning

Deep Reinforcement Learning (DRL) is a promising approach for teaching r...

0 Abdalkarim Mohtasib, et al. ∙

∙ 07/01/2021

Neural Task Success Classifiers for Robotic Manipulation from Few Real Demonstrations

Robots learning a new manipulation task from a small amount of demonstra...

6 Abdalkarim Mohtasib, et al. ∙

∙ 01/01/2021

A Survey on Deep Reinforcement Learning for Audio-Based Applications

Deep reinforcement learning (DRL) is poised to revolutionise the field o...

0 Siddique Latif, et al. ∙

∙ 08/27/2019

Ensemble-Based Deep Reinforcement Learning for Chatbots

Trainable chatbots that exhibit fluent and human-like conversations rema...

0 Heriberto Cuayáhuitl, et al. ∙

∙ 08/27/2019

A Data-Efficient Deep Learning Approach for Deployable Multimodal Social Robots

The deep supervised and reinforcement learning paradigms (among others) ...

11 Heriberto Cuayáhuitl, et al. ∙

∙ 08/27/2019

Deep Reinforcement Learning for Chatbots Using Clustered Actions and Human-Likeness Rewards

Training chatbots using the reinforcement learning paradigm is challengi...

44 Heriberto Cuayáhuitl, et al. ∙

∙ 12/02/2018

A Study on Dialogue Reward Prediction for Open-Ended Conversational Agents

The amount of dialogue history to include in a conversational agent is o...

0 Heriberto Cuayáhuitl, et al. ∙

∙ 11/26/2016

Deep Reinforcement Learning for Multi-Domain Dialogue Systems

Standard deep reinforcement learning methods such as Deep Q-Networks (DQ...

0 Heriberto Cuayáhuitl, et al. ∙

∙ 11/26/2016

Training an Interactive Humanoid Robot Using Multimodal Deep Reinforcement Learning

Training robots to perceive, act and communicate using multiple modaliti...

0 Heriberto Cuayáhuitl, et al. ∙

∙ 01/18/2016

SimpleDS: A Simple Deep Reinforcement Learning Dialogue System

This paper presents 'SimpleDS', a simple and publicly available dialogue...

0 Heriberto Cuayáhuitl, et al. ∙

∙ 11/25/2015

Strategic Dialogue Management via Deep Reinforcement Learning

Artificially intelligent agents equipped with strategic skills that can ...

0 Heriberto Cuayáhuitl, et al. ∙

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