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ORCIDNgo Anh Vien
Person information
- affiliation: Queen's University Belfast, UK
- affiliation: University of Stuttgart, Machine Learning and Robotics Lab, Germany
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Journal Articles
- 2023
[j22]Fabian Duffhauss
, Sebastian Koch, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
SyMFM6D: Symmetry-Aware Multi-Directional Fusion for Multi-View 6D Object Pose Estimation. IEEE Robotics Autom. Lett. 8(9): 5315-5322 (2023)- 2021
- [j21]Khoi Khac Nguyen, Ngo Anh Vien, Long Dinh Nguyen, Minh-Tuan Le, Lajos Hanzo, Trung Q. Duong:
Real-Time Energy Harvesting Aided Scheduling in UAV-Assisted D2D Networks Relying on Deep Reinforcement Learning. IEEE Access 9: 3638-3648 (2021) - [j20]Viet-Hung Dang, Ngo Anh Vien, TaeChoong Chung:
Constrained representation learning for recurrent policy optimisation under uncertainty. Adapt. Behav. 29(3) (2021) - [j19]Thien Van Luong, Youngwook Ko, Michail Matthaiou, Ngo Anh Vien, Minh-Tuan Le, Vu-Duc Ngo:
Deep Learning-Aided Multicarrier Systems. IEEE Trans. Wirel. Commun. 20(3): 2109-2119 (2021) - 2020
- [j18]Dang Quang Nguyen, Ngo Anh Vien, Viet-Hung Dang, TaeChoong Chung:
Asynchronous framework with Reptile+ algorithm to meta learn partially observable Markov decision process. Appl. Intell. 50(11): 4050-4062 (2020) - [j17]Viet-Hung Dang, Hoang Huu Viet, Nguyen Duc Thang, Ngo Anh Vien, Le Anh Tuan:
Improving Path Planning Methods in 2D Grid Maps. J. Comput. 15(1): 1-9 (2020) - [j16]Thien Van Luong, Youngwook Ko, Ngo Anh Vien, Michail Matthaiou, Hien Quoc Ngo:
Deep Energy Autoencoder for Noncoherent Multicarrier MU-SIMO Systems. IEEE Trans. Wirel. Commun. 19(6): 3952-3962 (2020) - 2019
- [j15]Khoi Khac Nguyen, Trung Quang Duong, Ngo Anh Vien, Nhien-An Le-Khac, Minh-Nghia Nguyen:
Non-Cooperative Energy Efficient Power Allocation Game in D2D Communication: A Multi-Agent Deep Reinforcement Learning Approach. IEEE Access 7: 100480-100490 (2019) - [j14]Khoi Khac Nguyen, Trung Q. Duong, Ngo Anh Vien, Nhien-An Le-Khac, Long Dinh Nguyen:
Distributed Deep Deterministic Policy Gradient for Power Allocation Control in D2D-Based V2V Communications. IEEE Access 7: 164533-164543 (2019) - [j13]Tuyen Pham Le, Ngo Anh Vien, P. Marlith Jaramillo, TaeChoong Chung:
Importance sampling policy gradient algorithms in reproducing kernel Hilbert space. Artif. Intell. Rev. 52(3): 2039-2059 (2019) - [j12]Viet-Hung Dang, Ngo Anh Vien, TaeChoong Chung:
A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space. Genet. Program. Evolvable Mach. 20(4): 479-501 (2019) - [j11]Thien Van Luong, Youngwook Ko, Ngo Anh Vien, Duy H. N. Nguyen, Michail Matthaiou:
Deep Learning-Based Detector for OFDM-IM. IEEE Wirel. Commun. Lett. 8(4): 1159-1162 (2019) - 2018
- [j10]Tuyen Pham Le, Ngo Anh Vien, TaeChoong Chung:
A Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes. IEEE Access 6: 49089-49102 (2018) - 2017
- [j9]Peter Englert, Ngo Anh Vien, Marc Toussaint:
Inverse KKT: Learning cost functions of manipulation tasks from demonstrations. Int. J. Robotics Res. 36(13-14): 1474-1488 (2017) - 2016
- [j8]Ngo Anh Vien, SeungGwan Lee, TaeChoong Chung:
Bayes-adaptive hierarchical MDPs. Appl. Intell. 45(1): 112-126 (2016) - 2014
- [j7]Ngo Anh Vien, Hung Quoc Ngo, Sungyoung Lee, TaeChoong Chung:
Approximate planning for bayesian hierarchical reinforcement learning. Appl. Intell. 41(3): 808-819 (2014) - [j6]Hung Quoc Ngo, Matthew D. Luciw, Jawad Nagi, Alexander Förster, Jürgen Schmidhuber, Ngo Anh Vien:
Efficient Interactive Multiclass Learning from Binary Feedback. ACM Trans. Interact. Intell. Syst. 4(3): 12:1-12:25 (2014) - 2013
- [j5]Ngo Anh Vien, Wolfgang Ertel, TaeChoong Chung:
Learning via human feedback in continuous state and action spaces. Appl. Intell. 39(2): 267-278 (2013) - [j4]Ngo Anh Vien, Wolfgang Ertel, Viet-Hung Dang, TaeChoong Chung:
Monte-Carlo tree search for Bayesian reinforcement learning. Appl. Intell. 39(2): 345-353 (2013) - 2011
- [j3]Ngo Anh Vien, Hwanjo Yu, TaeChoong Chung:
Hessian matrix distribution for Bayesian policy gradient reinforcement learning. Inf. Sci. 181(9): 1671-1685 (2011) - 2010
- [j2]Ngo Anh Vien, SeungGwan Lee, TaeChoong Chung:
Policy Gradient Based Semi-Markov Decision Problems: Approximation and Estimation Errors. IEICE Trans. Inf. Syst. 93-D(2): 271-279 (2010) - 2009
- [j1]Ngo Anh Vien, Nguyen Hoang Viet, SeungGwan Lee, TaeChoong Chung:
Policy Gradient SMDP for Resource Allocation and Routing in Integrated Services Networks. IEICE Trans. Commun. 92-B(6): 2008-2022 (2009)
Conference and Workshop Papers
- 2023
- [c40]Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects. CoRL 2023: 1572-1595 - [c39]Philipp Schillinger, Miroslav Gabriel, Alexander Kuss, Hanna Ziesche, Ngo Anh Vien:
Model-Free Grasping with Multi-Suction Cup Grippers for Robotic Bin Picking. IROS 2023: 3107-3113 - 2022
- [c38]Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
Deep Black-Box Reinforcement Learning with Movement Primitives. CoRL 2022: 1244-1265 - [c37]Ning Gao, Hanna Ziesche, Ngo Anh Vien, Michael Volpp, Gerhard Neumann:
What Matters For Meta-Learning Vision Regression Tasks? CVPR 2022: 14756-14766 - [c36]Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion. ECCV (39) 2022: 674-691 - [c35]Oussama Zenkri, Ngo Anh Vien, Gerhard Neumann:
Hierarchical Policy Learning for Mechanical Search. ICRA 2022: 1954-1960 - [c34]Zohar Feldman, Hanna Ziesche, Ngo Anh Vien, Dotan Di Castro:
A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives. ICRA 2022: 6365-6371 - 2021
- [c33]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Maria Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. ICLR 2021 - [c32]Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann:
Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty. IROS 2021: 2383-2390 - [c31]Dianhao Zhang, Ngo Anh Vien, Mien Van, Seán F. McLoone:
Non-local Graph Convolutional Network for joint Activity Recognition and Motion Prediction. IROS 2021: 2970-2977 - 2020
- [c30]Abdullahi Abubakar, Sakil Barbhuiya, Peter Kilpatrick, Ngo Anh Vien, Dimitrios S. Nikolopoulos:
Fast Analysis and Prediction in Large Scale Virtual Machines Resource Utilisation. CLOSER 2020: 115-126 - [c29]Tai Hoang, Ngo Anh Vien:
Graph-Based Motion Planning Networks. ECML/PKDD (2) 2020: 557-573 - 2018
- [c28]Ngo Anh Vien, Heiko Zimmermann, Marc Toussaint:
Bayesian Functional Optimization. AAAI 2018: 4171-4178 - [c27]Minh-Nghia Nguyen, Ngo Anh Vien:
Scalable and Interpretable One-Class SVMs with Deep Learning and Random Fourier Features. ECML/PKDD (1) 2018: 157-172 - 2017
- [c26]Ngo Anh Vien, Viet-Hung Dang, TaeChoong Chung:
A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space. ACML 2017: 606-621 - [c25]Viet-Hung Dang, Ngo Anh Vien, Pham Le-Tuyen, TaeChoong Chung:
A Functional Optimization Method for Continuous Domains. INISCOM 2017: 254-265 - [c24]Le Pham Tuyen, Md. Abu Layek, Ngo Anh Vien, TaeChoong Chung:
Deep reinforcement learning algorithms for steering an underactuated ship. MFI 2017: 602-607 - 2016
- [c23]Marc Toussaint, Thibaut Munzer, Yoan Mollard, Li Yang Wu, Ngo Anh Vien, Manuel Lopes:
Relational activity processes for modeling concurrent cooperation. ICRA 2016: 5505-5511 - [c22]Ngo Anh Vien, Peter Englert, Marc Toussaint:
Policy Search in Reproducing Kernel Hilbert Space. IJCAI 2016: 2089-2096 - 2015
- [c21]Ngo Anh Vien, Marc Toussaint:
Hierarchical Monte-Carlo Planning. AAAI 2015: 3613-3619 - [c20]Ngo Anh Vien, Marc Toussaint:
Touch based POMDP manipulation via sequential submodular optimization. Humanoids 2015: 407-413 - [c19]Ngo Anh Vien, Marc Toussaint:
POMDP manipulation via trajectory optimization. IROS 2015: 242-249 - 2014
- [c18]Ngo Anh Vien, Hung Quoc Ngo, Wolfgang Ertel:
Monte carlo bayesian hierarchical reinforcement learning. AAMAS 2014: 1551-1552 - [c17]Ngo Anh Vien, Marc Toussaint:
Model-Based Relational RL When Object Existence is Partially Observable. ICML 2014: 559-567 - 2013
- [c16]Ngo Anh Vien, Marc Toussaint:
Reasoning with Uncertainties Over Existence of Objects. AAAI Fall Symposia 2013 - [c15]Hung Quoc Ngo, Matthew David Luciw, Ngo Anh Vien, Jürgen Schmidhuber:
Upper Confidence Weighted Learning for Efficient Exploration in Multiclass Prediction with Binary Feedback. IJCAI 2013: 2488-2494 - 2012
- [c14]Ngo Anh Vien, Wolfgang Ertel:
Learning via Human Feedback in Continuous State and Action Spaces. AAAI Fall Symposium: Robots Learning Interactively from Human Teachers 2012 - [c13]Ngo Anh Vien, Wolfgang Ertel:
Reinforcement learning combined with human feedback in continuous state and action spaces. ICDL-EPIROB 2012: 1-6 - [c12]Ngo Anh Vien, Wolfgang Ertel:
Monte Carlo Tree Search for Bayesian Reinforcement Learning. ICMLA (1) 2012: 138-143 - 2011
- [c11]Nguyen Thi Thanh Thuy, Nguyen Thi Ngoc Vinh, Ngo Anh Vien:
Nomogram Visualization for Ranking Support Vector Machine. ISNN (2) 2011: 94-102 - 2010
- [c10]Haoyu Bai, David Hsu, Wee Sun Lee, Ngo Anh Vien:
Monte Carlo Value Iteration for Continuous-State POMDPs. WAFR 2010: 175-191 - 2009
- [c9]Ngo Anh Vien, Nguyen Hoang Viet, TaeChoong Chung, Hwanjo Yu, Sungchul Kim, Baek Hwan Cho:
VRIFA: a nonlinear SVM visualization tool using nomogram and localized radial basis function (LRBF) kernels. CIKM 2009: 2081-2082 - [c8]Nguyen Thi Thanh Thuy, Ngo Anh Vien, Nguyen Hoang Viet, TaeChoong Chung:
Probabilistic Ranking Support Vector Machine. ISNN (2) 2009: 345-353 - 2008
- [c7]Nguyen Hoang Viet, Ngo Anh Vien, SeungGwan Lee, TaeChoong Chung:
Obstacle Avoidance Path Planning for Mobile Robot Based on Multi Colony Ant Algorithm. ACHI 2008: 285-289 - [c6]Nguyen Hoang Viet, Ngo Anh Vien, SeungGwan Lee, TaeChoong Chung:
Efficient Distributed Sensor Dispatch in Mobile Sensor Network. AINA Workshops 2008: 1561-1566 - [c5]Nguyen Hoang Viet, Ngo Anh Vien, TaeChoong Chung:
Policy Gradient SMDP for Resource Allocation and Routing in Integrated Services Networks. ICNSC 2008: 1541-1546 - [c4]Ngo Anh Vien, TaeChoong Chung:
Policy Gradient Semi-markov Decision Process. ICTAI (2) 2008: 11-18 - 2007
- [c3]Ngo Anh Vien, TaeChoong Chung:
Natural Gradient Policy for Average Cost SMDP Problem. ICTAI (1) 2007: 11-18 - [c2]Ngo Anh Vien, Nguyen Hoang Viet, SeungGwan Lee, TaeChoong Chung:
Obstacle Avoidance Path Planning for Mobile Robot Based on Ant-Q Reinforcement Learning Algorithm. ISNN (1) 2007: 704-713 - [c1]Ngo Anh Vien, Nguyen Hoang Viet, SeungGwan Lee, TaeChoong Chung:
Heuristic Search Based Exploration in Reinforcement Learning. IWANN 2007: 110-118
Informal and Other Publications
- 2024
- [i21]Huy Le, Philipp Schillinger, Miroslav Gabriel, Alexander Qualmann, Ngo Anh Vien:
Pseudo-Labeling and Contextual Curriculum Learning for Online Grasp Learning in Robotic Bin Picking. CoRR abs/2403.02495 (2024) - 2023
- [i20]Fabian Duffhauss, Sebastian Koch, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimation. CoRR abs/2307.00306 (2023) - [i19]Philipp Schillinger, Miroslav Gabriel, Alexander Kuss, Hanna Ziesche, Ngo Anh Vien:
Model-free Grasping with Multi-Suction Cup Grippers for Robotic Bin Picking. CoRR abs/2307.16488 (2023) - [i18]Philipp Blättner, Johannes Brand, Gerhard Neumann, Ngo Anh Vien:
DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes. CoRR abs/2308.00456 (2023) - [i17]Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects. CoRR abs/2308.16528 (2023) - [i16]Yitian Shi, Philipp Schillinger, Miroslav Gabriel, Alexander Kuss, Zohar Feldman, Hanna Ziesche, Ngo Anh Vien:
Uncertainty-driven Exploration Strategies for Online Grasp Learning. CoRR abs/2309.12038 (2023) - 2022
- [i15]Oussama Zenkri, Ngo Anh Vien, Gerhard Neumann:
Hierarchical Policy Learning for Mechanical Search. CoRR abs/2202.13680 (2022) - [i14]Ning Gao, Hanna Ziesche, Ngo Anh Vien, Michael Volpp, Gerhard Neumann:
What Matters For Meta-Learning Vision Regression Tasks? CoRR abs/2203.04905 (2022) - [i13]Ruijie Chen, Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
Meta-Learning Regrasping Strategies for Physical-Agnostic Objects. CoRR abs/2205.11110 (2022) - [i12]Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion. CoRR abs/2209.11277 (2022) - [i11]Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
Deep Black-Box Reinforcement Learning with Movement Primitives. CoRR abs/2210.09622 (2022) - [i10]Ilyes Toumi, Andreas Orthey, Alexander von Rohr, Ngo Anh Vien:
Multi-Arm Bin-Picking in Real-Time: A Combined Task and Motion Planning Approach. CoRR abs/2211.11089 (2022) - 2021
- [i9]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. CoRR abs/2101.09207 (2021) - [i8]Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann:
Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty. CoRR abs/2106.04306 (2021) - [i7]Ngo Anh Vien, Gerhard Neumann:
Differentiable Robust LQR Layers. CoRR abs/2106.05535 (2021) - [i6]Dianhao Zhang, Ngo Anh Vien, Mien Van, Seán F. McLoone:
Non-local Graph Convolutional Network for joint Activity Recognition and Motion Prediction. CoRR abs/2108.01518 (2021) - [i5]Zohar Feldman, Hanna Ziesche, Ngo Anh Vien, Dotan Di Castro:
A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives. CoRR abs/2111.01510 (2021) - 2020
- [i4]Thien Van Luong, Youngwook Ko, Ngo Anh Vien, Michail Matthaiou, Hien Quoc Ngo:
Deep Energy Autoencoder for Noncoherent Multicarrier MU-SIMO Systems. CoRR abs/2002.08710 (2020) - [i3]Tai Hoang, Ngo Anh Vien:
Bayes-Adaptive Deep Model-Based Policy Optimisation. CoRR abs/2010.15948 (2020) - 2018
- [i2]Minh-Nghia Nguyen, Ngo Anh Vien:
Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features. CoRR abs/1804.04888 (2018) - [i1]Le Pham Tuyen, Ngo Anh Vien, Md. Abu Layek, TaeChoong Chung:
Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes. CoRR abs/1805.04419 (2018)
Coauthor Index
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