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Inverse KKT: Learning cost functions of manipulation tasks from demonstrations

The International journal of robotics research, 2017-12, Vol.36 (13-14), p.1474-1488

2017

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Importance sampling policy gradient algorithms in reproducing kernel Hilbert space

The Artificial intelligence review, 2019-10, Vol.52 (3), p.2039-2059

2019

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Deep Energy Autoencoder for Noncoherent Multicarrier MU-SIMO Systems

IEEE transactions on wireless communications, 2020-06, Vol.19 (6), p.3952-3962

2020

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Deep Learning-Aided Multicarrier Systems

IEEE transactions on wireless communications, 2021-03, Vol.20 (3), p.2109-2119

2021

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Deep Learning-Based Detector for OFDM-IM

IEEE wireless communications letters, 2019-08, Vol.8 (4), p.1159-1162

2019

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What Matters For Meta-Learning Vision Regression Tasks?

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, p.14756-14766

2022

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A Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes

IEEE access, 2018-01, Vol.6, p.49089-49102

2018

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Non-Cooperative Energy Efficient Power Allocation Game in D2D Communication: A Multi-Agent Deep Reinforcement Learning Approach

IEEE access, 2019, Vol.7, p.100480-100490

2019

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Graph-Based Motion Planning Networks

Machine Learning and Knowledge Discovery in Databases, p.557-573

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Non-local Graph Convolutional Network for joint Activity Recognition and Motion Prediction

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, p.2970-2977

2021

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Constrained representation learning for recurrent policy optimisation under uncertainty

Adaptive behavior, 2021-06, Vol.29 (3), p.253-265

2021

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Hessian matrix distribution for Bayesian policy gradient reinforcement learning

Information sciences, 2011-05, Vol.181 (9), p.1671-1685

2011

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A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space

Genetic programming and evolvable machines, 2019-12, Vol.20 (4), p.479-501

2019

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Distributed Deep Deterministic Policy Gradient for Power Allocation Control in D2D-Based V2V Communications

IEEE access, 2019, Vol.7, p.164533-164543

2019

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Asynchronous framework with Reptile+ algorithm to meta learn partially observable Markov decision process

Applied intelligence (Dordrecht, Netherlands), 2020-11, Vol.50 (11), p.4050-4062

2020

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Real-Time Energy Harvesting Aided Scheduling in UAV-Assisted D2D Networks Relying on Deep Reinforcement Learning

IEEE access, 2021, Vol.9, p.3638-3648

2021

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Learning via human feedback in continuous state and action spaces

Applied intelligence (Dordrecht, Netherlands), 2013-09, Vol.39 (2), p.267-278

2013

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Bayes-adaptive hierarchical MDPs

Applied intelligence (Dordrecht, Netherlands), 2016-07, Vol.45 (1), p.112-126

2016

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POMDP manipulation via trajectory optimization

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, p.242-249

2015

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FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion

Computer Vision - ECCV 2022, 2022, Vol.13699, p.674-691

2022

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Approximate planning for bayesian hierarchical reinforcement learning

Applied intelligence (Dordrecht, Netherlands), 2014-10, Vol.41 (3), p.808-819

2014

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Relational activity processes for modeling concurrent cooperation

2016 IEEE International Conference on Robotics and Automation (ICRA), 2016, p.5505-5511

2016

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Monte-Carlo tree search for Bayesian reinforcement learning

Applied intelligence (Dordrecht, Netherlands), 2013-09, Vol.39 (2), p.345-353

2013

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A Functional Optimization Method for Continuous Domains

Industrial Networks and Intelligent Systems, p.254-265

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Hierarchical Policy Learning for Mechanical Search

2022 International Conference on Robotics and Automation (ICRA), 2022, p.1954-1960

2022

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Inverse KKT: Learning cost functions of manipulation tasks from demonstrations

Importance sampling policy gradient algorithms in reproducing kernel Hilbert space

Deep Energy Autoencoder for Noncoherent Multicarrier MU-SIMO Systems

Deep Learning-Aided Multicarrier Systems

Deep Learning-Based Detector for OFDM-IM

What Matters For Meta-Learning Vision Regression Tasks?

A Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes

Non-Cooperative Energy Efficient Power Allocation Game in D2D Communication: A Multi-Agent Deep Reinforcement Learning Approach

Graph-Based Motion Planning Networks

Non-local Graph Convolutional Network for joint Activity Recognition and Motion Prediction

Constrained representation learning for recurrent policy optimisation under uncertainty

Hessian matrix distribution for Bayesian policy gradient reinforcement learning

A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space

Distributed Deep Deterministic Policy Gradient for Power Allocation Control in D2D-Based V2V Communications

Asynchronous framework with Reptile+ algorithm to meta learn partially observable Markov decision process

Real-Time Energy Harvesting Aided Scheduling in UAV-Assisted D2D Networks Relying on Deep Reinforcement Learning

Learning via human feedback in continuous state and action spaces

Bayes-adaptive hierarchical MDPs

POMDP manipulation via trajectory optimization

FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion

Approximate planning for bayesian hierarchical reinforcement learning

Relational activity processes for modeling concurrent cooperation

Monte-Carlo tree search for Bayesian reinforcement learning

A Functional Optimization Method for Continuous Domains

Hierarchical Policy Learning for Mechanical Search

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