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Peter Vrancx
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2020 – today
- 2024
- [j12]Diana Gomes, Kyriakos Efthymiadis, Ann Nowé, Peter Vrancx:
Depth Scaling in Graph Neural Networks: Understanding the Flat Curve Behavior. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [c39]Diksha Moolchandani
, Joyjit Kundu, Frederik Ruelens, Peter Vrancx, Timon Evenblij
, Manu Perumkunnil:
AMPeD: An Analytical Model for Performance in Distributed Training of Transformers. ISPASS 2023: 306-315 - 2022
- [j11]Nathan Laubeuf
, Jonas Doevenspeck, Ioannis A. Papistas, Michele Caselli
, Stefan Cosemans, Peter Vrancx, Debjyoti Bhattacharjee
, Arindam Mallik, Peter Debacker, Diederik Verkest, Francky Catthoor, Rudy Lauwereins:
Dynamic Quantization Range Control for Analog-in-Memory Neural Networks Acceleration. ACM Trans. Design Autom. Electr. Syst. 27(5): 46:1-46:21 (2022) - [c38]Nitish Satya Murthy, Peter Vrancx, Nathan Laubeuf, Peter Debacker, Francky Catthoor, Marian Verhelst
:
Learn to Learn on Chip: Hardware-aware Meta-learning for Quantized Few-shot Learning at the Edge. SEC 2022: 14-25 - [c37]Kodai Ueyoshi, Ioannis A. Papistas, Pouya Houshmand, Giuseppe Maria Sarda
, Vikram Jain
, Man Shi, Qilin Zheng, Juan Sebastian Piedrahita Giraldo, Peter Vrancx, Jonas Doevenspeck, Debjyoti Bhattacharjee
, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst
:
DIANA: An End-to-End Energy-Efficient Digital and ANAlog Hybrid Neural Network SoC. ISSCC 2022: 1-3 - 2021
- [c36]Jonas Doevenspeck, Peter Vrancx, Nathan Laubeuf, Arindam Mallik, Peter Debacker, Diederik Verkest, Rudy Lauwereins, Wim Dehaene:
Noise tolerant ternary weight deep neural networks for analog in-memory inference. IJCNN 2021: 1-8 - [i15]John McLeod, Hrvoje Stojic, Vincent Adam, Dongho Kim, Jordi Grau-Moya, Peter Vrancx, Felix Leibfried:
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow. CoRR abs/2103.14407 (2021) - 2020
- [c35]Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim:
Batch Reinforcement Learning with Hyperparameter Gradients. ICML 2020: 5725-5735
2010 – 2019
- 2019
- [c34]Jordi Grau-Moya, Felix Leibfried, Peter Vrancx:
Soft Q-Learning with Mutual-Information Regularization. ICLR (Poster) 2019 - [c33]Anna Harutyunyan, Peter Vrancx, Philippe Hamel, Ann Nowé, Doina Precup:
Per-Decision Option Discounting. ICML 2019: 2644-2652 - [i14]Janith C. Petangoda, Sergio Pascual-Diaz, Vincent Adam, Peter Vrancx, Jordi Grau-Moya:
Disentangled Skill Embeddings for Reinforcement Learning. CoRR abs/1906.09223 (2019) - [i13]Marcin B. Tomczak, Dongho Kim, Peter Vrancx, Kee-Eung Kim:
Policy Optimization Through Approximated Importance Sampling. CoRR abs/1910.03857 (2019) - [i12]Marcin B. Tomczak, Sergio Valcarcel Macua, Enrique Munoz de Cote, Peter Vrancx:
Compatible features for Monotonic Policy Improvement. CoRR abs/1910.03880 (2019) - 2018
- [j10]Christopher Amato
, Haitham Bou-Ammar, Elizabeth F. Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, William F. Lawless, Francesca Rossi, Frans A. Oliehoek
, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Karl Tuyls, Philip van Allen, Kristen Brent Venable, Peter Vrancx, Shiqi Zhang:
Reports on the 2018 AAAI Spring Symposium Series. AI Mag. 39(4): 29-35 (2018) - [j9]Bert J. Claessens, Peter Vrancx, Frederik Ruelens
:
Convolutional Neural Networks for Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control. IEEE Trans. Smart Grid 9(4): 3259-3269 (2018) - [c32]Anna Harutyunyan, Peter Vrancx, Pierre-Luc Bacon, Doina Precup, Ann Nowé:
Learning With Options That Terminate Off-Policy. AAAI 2018: 3173-3182 - [c31]Denis Steckelmacher, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Hélène Plisnier, Ann Nowé:
Reinforcement Learning in POMDPs With Memoryless Options and Option-Observation Initiation Sets. AAAI 2018: 4099-4106 - [i11]Garrett Andersen, Peter Vrancx, Haitham Bou-Ammar:
Learning High-level Representations from Demonstrations. CoRR abs/1802.06604 (2018) - [i10]Felix Leibfried, Rasul Tutunov, Peter Vrancx, Haitham Bou-Ammar:
Model-Based Stabilisation of Deep Reinforcement Learning. CoRR abs/1809.01906 (2018) - 2017
- [j8]Tim Brys, Anna Harutyunyan, Peter Vrancx, Ann Nowé
, Matthew E. Taylor:
Multi-objectivization and ensembles of shapings in reinforcement learning. Neurocomputing 263: 48-59 (2017) - [c30]Pieter Libin
, Timothy Verstraeten
, Kristof Theys
, Diederik M. Roijers
, Peter Vrancx
, Ann Nowé
:
Efficient Evaluation of Influenza Mitigation Strategies Using Preventive Bandits. AAMAS Workshops (Visionary Papers) 2017: 67-85 - [c29]Roxana Radulescu, Peter Vrancx, Ann Nowé:
Analysing Congestion Problems in Multi-agent Reinforcement Learning. AAMAS 2017: 1705-1707 - [i9]Roxana Radulescu, Peter Vrancx, Ann Nowé:
Analysing Congestion Problems in Multi-agent Reinforcement Learning. CoRR abs/1702.08736 (2017) - [i8]Frederik Ruelens, Bert J. Claessens, Peter Vrancx, Fred Spiessens, Geert Deconinck:
Direct Load Control of Thermostatically Controlled Loads Based on Sparse Observations Using Deep Reinforcement Learning. CoRR abs/1707.08553 (2017) - [i7]Denis Steckelmacher
, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Ann Nowé:
Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets. CoRR abs/1708.06551 (2017) - [i6]Jesus Lago, Fjo De Ridder, Peter Vrancx, Bart De Schutter:
Forecasting day-ahead electricity prices in Europe: the importance of considering market integration. CoRR abs/1708.07061 (2017) - [i5]Anna Harutyunyan, Peter Vrancx, Pierre-Luc Bacon, Doina Precup, Ann Nowé:
Learning with Options that Terminate Off-Policy. CoRR abs/1711.03817 (2017) - 2016
- [j7]Peter Vrancx, Enda Howley
, Matt Knudson:
Preface to the special issue: adaptive learning agents. Knowl. Eng. Rev. 31(1): 1-2 (2016) - [j6]Abdel Rodríguez
, Peter Vrancx, Ricardo Grau, Ann Nowé
:
A reinforcement learning approach to coordinate exploration with limited communication in continuous action games. Knowl. Eng. Rev. 31(1): 77-95 (2016) - [j5]Kevin Tanghe, Anna Harutyunyan, Erwin Aertbeliën
, Friedl De Groote
, Joris De Schutter
, Peter Vrancx, Ann Nowé
:
Predicting Seat-Off and Detecting Start-of-Assistance Events for Assisting Sit-to-Stand With an Exoskeleton. IEEE Robotics Autom. Lett. 1(2): 792-799 (2016) - [i4]Bert J. Claessens, Peter Vrancx, Frederik Ruelens:
Convolutional Neural Networks For Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control. CoRR abs/1604.08382 (2016) - 2015
- [j4]Peter Vrancx, Pasquale Gurzi, Abdel Rodríguez
, Kris Steenhaut
, Ann Nowé
:
A Reinforcement Learning Approach for Interdomain Routing with Link Prices. ACM Trans. Auton. Adapt. Syst. 10(1): 5:1-5:26 (2015) - [c28]Anna Harutyunyan, Sam Devlin, Peter Vrancx, Ann Nowé:
Expressing Arbitrary Reward Functions as Potential-Based Advice. AAAI 2015: 2652-2658 - [c27]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Multi-Scale Reward Shaping via an Off-Policy Ensemble. AAMAS 2015: 1641-1642 - [c26]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Shaping Mario with Human Advice. AAMAS 2015: 1913-1914 - [i3]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Off-Policy Reward Shaping with Ensembles. CoRR abs/1502.03248 (2015) - [i2]Denis Steckelmacher, Peter Vrancx:
An Empirical Comparison of Neural Architectures for Reinforcement Learning in Partially Observable Environments. CoRR abs/1512.05509 (2015) - 2014
- [c25]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Off-Policy Shaping Ensembles in Reinforcement Learning. ECAI 2014: 1021-1022 - [c24]Tim Brys, Anna Harutyunyan, Peter Vrancx, Matthew E. Taylor
, Daniel Kudenko, Ann Nowé:
Multi-objectivization of reinforcement learning problems by reward shaping. IJCNN 2014: 2315-2322 - [c23]Kristof Van Moffaert, Kevin Van Vaerenbergh, Peter Vrancx, Ann Nowé
:
Multi-objective χ-Armed bandits. IJCNN 2014: 2331-2338 - [i1]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Off-Policy Shaping Ensembles in Reinforcement Learning. CoRR abs/1405.5358 (2014) - 2013
- [c22]Abdel Rodríguez
, Peter Vrancx, Ann Nowé, Erik Hostens:
Model-free learning of wire winding control. ASCC 2013: 1-6 - [c21]Kristof Van Moffaert, Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Reinforcement Learning for Multi-purpose Schedules. ICAART (2) 2013: 203-209 - 2012
- [c20]Abdel Rodríguez, Peter Vrancx, Ricardo Grau Ábalo, Ann Nowé:
An RL approach to common-interest continuous action games. AAMAS 2012: 1401-1402 - [c19]Kevin Van Vaerenbergh, Abdel Rodríguez
, Matteo Gagliolo
, Peter Vrancx, Ann Nowé, Julian Stoev, Stijn Goossens, Gregory Pinte, Wim Symens:
Improving wet clutch engagement with reinforcement learning. IJCNN 2012: 1-8 - [p2]Ann Nowé, Peter Vrancx, Yann-Michaël De Hauwere:
Game Theory and Multi-agent Reinforcement Learning. Reinforcement Learning 2012: 441-470 - [e1]Peter Vrancx, Matthew Knudson, Marek Grzes:
Adaptive and Learning Agents - International Workshop, ALA 2011, Held at AAMAS 2011, Taipei, Taiwan, May 2, 2011, Revised Selected Papers. Lecture Notes in Computer Science 7113, Springer 2012, ISBN 978-3-642-28498-4 [contents] - 2011
- [c18]Yann-Michaël De Hauwere, Peter Vrancx
, Ann Nowé:
Solving Sparse Delayed Coordination Problems in Multi-Agent Reinforcement Learning. ALA 2011: 114-133 - [c17]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Solving delayed coordination problems in MAS. AAMAS 2011: 1115-1116 - [c16]Tim Brys, Yann-Michaël De Hauwere, Ann Nowé, Peter Vrancx
:
Local Coordination in Online Distributed Constraint Optimization Problems. EUMAS 2011: 31-47 - [c15]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Adaptive State Representations for Multi-agent Reinforcement Learning. ICAART (2) 2011: 181-189 - [c14]Peter Vrancx, Yann-Michaël De Hauwere, Ann Nowé:
Transfer Learning for Multi-agent Coordination. ICAART (2) 2011: 263-272 - [c13]Pasquale Gurzi, Kris Steenhaut, Ann Nowé, Peter Vrancx:
Learning a pricing strategy in multi-domain DWDM networks. LANMAN 2011: 1-6 - 2010
- [j3]Yann-Michaël De Hauwere, Peter Vrancx
, Ann Nowé:
Generalized learning automata for multi-agent reinforcement learning. AI Commun. 23(4): 311-324 (2010) - [j2]Peter Vrancx
, Katja Verbeeck, Ann Nowé:
Analyzing the dynamics of stigmergetic interactions through pheromone games. Theor. Comput. Sci. 411(21): 2116-2126 (2010) - [c12]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Learning multi-agent state space representations. AAMAS 2010: 715-722 - [c11]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Taking turns in general sum Markov games. AAMAS 2010: 1439-1440 - [p1]Yann-Michaël De Hauwere, Peter Vrancx
, Ann Nowé:
Multi-Agent Systems and Large State Spaces. Agent and Multi-agent Technology for Internet and Enterprise Systems 2010: 181-205
2000 – 2009
- 2008
- [j1]Peter Vrancx
, Katja Verbeeck, Ann Nowé:
Decentralized Learning in Markov Games. IEEE Trans. Syst. Man Cybern. Part B 38(4): 976-981 (2008) - [c10]Peter Vrancx, Karl Tuyls
, Ronald L. Westra:
Switching dynamics of multi-agent learning. AAMAS (1) 2008: 307-313 - [c9]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Using Generalized Learning Automata for State Space Aggregation in MAS. KES (1) 2008: 182-193 - 2007
- [c8]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Networks of Learning Automata and Limiting Games. Adaptive Agents and Multi-Agents Systems 2007: 224-238 - [c7]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Optimal Convergence in Multi-Agent MDPs. KES (3) 2007: 107-114 - 2006
- [c6]Peter Vrancx, Ann Nowé:
Using Pheromone Repulsion to Find Disjoint Paths. ANTS Workshop 2006: 522-523 - [c5]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Analyzing Stigmergetic Algorithms Through Automata Games. KDECB 2006: 145-156 - 2005
- [c4]Peter Vrancx, Ann Nowé, Kris Steenhaut:
Multi-type ACO for light path protection. EUMAS 2005: 513 - [c3]Rafael Bello
, Ann Nowé, Yaile Caballero
, Yudel Gómez, Peter Vrancx
:
A model based on ant colony system and rough set theory to feature selection. GECCO 2005: 275-276 - [c2]Peter Vrancx
, Ann Nowé, Kris Steenhaut:
Multi-type ACO for Light Path Protection. LAMAS 2005: 207-215 - 2004
- [c1]Ann Nowé, Katja Verbeeck, Peter Vrancx:
Multi-type Ant Colony: The Edge Disjoint Paths Problem. ANTS Workshop 2004: 202-213
Coauthor Index
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last updated on 2024-08-10 00:30 CEST by the dblp team
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