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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 2024-10-07 22:16 CEST by the dblp team
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