Conference and journal papers
2024
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits Proceedings Article Forthcoming
In: ACM International Conference on Information and Knowledge Management, Forthcoming.
Accelerated Tsetlin Machine Inference Through Incremental Model Re-evaluation Proceedings Article Forthcoming
In: International Symposium on Tsetlin Machines, Forthcoming.
Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems Proceedings Article Forthcoming
In: International ACM SIGIR Conference on Research and Development in Information Retrieval, Forthcoming.
Planning with a Learned Policy Basis to Optimally Solve Complex Tasks Proceedings Article
In: International Conference on Automated Planning and Scheduling, 2024.
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments Proceedings Article
In: Artificial Agents and Multi-Agent Systems (AAMAS), 2024.
2023
Learning Hierarchical Planning-Based Policies from Offline Data Proceedings Article
In: Machine Learning and Knowledge Discovery in Databases: Research Track (ECML PKDD), 2023.
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes Proceedings Article
In: Machine Learning and Knowledge Discovery in Databases: Research Track (ECML PKDD), 2023.
Bridge the Inference Gaps of Neural Processes via Expectation Maximization Proceedings Article
In: International Conference on Learning Representations, 2023.
Reusable Options through Gradient-based Meta Learning Journal Article
In: Transactions on Machine Learning Research, vol. 03/2023, 2023.
2022
Learning Expressive Meta-Representations with Mixture of Expert Neural Processes Proceedings Article
In: Advances in Neural Information Processing Systems, 2022.
Neural Topological Ordering for Computation Graphs Proceedings Article
In: Advances in Neural Information Processing Systems, 2022.
Value Refinement Network (VRN) Proceedings Article
In: International Joint Conference on Artificial Intelligence, 2022.
Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods Proceedings Article
In: International Joint Conference on Artificial Intelligence, 2022.
Logic-based AI for Interpretable Board Game Winner Prediction with Tsetlin Machine Proceedings Article
In: International Joint Conference on Neural Networks, 2022.
Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search Proceedings Article
In: International Conference on Machine Learning, 2022.
Deep Policy Dynamic Programming for Vehicle Routing Problems Proceedings Article
In: International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2022.
Multi-Agent MDP Homomorphic Networks Proceedings Article
In: Proceedings of the International Conference on Learning Representations, 2022.
Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation Proceedings Article
In: AAAI National Conference on Artificial Intelligence, 2022.
2021
Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator Journal Article
In: Journal of Medical Systems, vol. 45, no. 102, 2021.
Deep Coherent Exploration For Continuous Control Proceedings Article
In: International Conference on Machine Learning, 2021.
Hierarchies of Planning and Reinforcement Learning for Robot Navigation Proceedings Article
In: IEEE International Conference on Robotics and Automation, 2021.
Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study Journal Article
In: International Journal of Environmental Research and Public Health, Special Issue, 2021.
2020
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning Proceedings Article
In: Advances in Neural Information Processing Systems, 2020.
Experimental design for MRI by greedy policy search Proceedings Article
In: Advances in Neural Information Processing Systems, 2020.
Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems Proceedings Article
In: The ACM Conference on Recommender Systems, 2020.
Social Navigation with Human Empowerment Driven Reinforcement Learning Proceedings Article
In: International Conference on Artificial Neural Networks, 2020.
In: Computer, vol. 53, no. 8, pp. 18–28, 2020.
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables Proceedings Article
In: International Conference on Machine Learning, 2020.
An Autonomous Free Airspace En-route Controller using Deep Reinforcement Learning Techniques Proceedings Article
In: International Conference on Research in Air Transportation, 2020.
A Performance-Based Start State Curriculum Framework for Reinforcement Learning Proceedings Article
In: International Conference on Autonomous Agents and Multi-Agent Systems, 2020.
Estimating Gradients for Discrete Random Variables by Sampling without Replacement Proceedings Article
In: International Conference on Learning Representations, 2020.
Ancestral Gumbel-Top-k Sampling for Sampling without Replacement Journal Article
In: Journal of Machine Learning Research, vol. 21, no. 47, pp. 1–36, 2020.
2019
Deep Generative Modeling of LiDAR Data Proceedings Article
In: IEEE International Conference on Intelligent Robots and Systems, 2019.
Stochastic Activation Actor Critic Methods Proceedings Article
In: European Conference on Machine Learning, 2019.
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement Proceedings Article
In: International Conference on Machine Learning, pp. 3499–3508, 2019.
Uncertainty aware Imitation Learning on Multiple Tasks using Bayesian Neural Networks Proceedings Article
In: International Conference on Robotics and Automation, 2019.
Attention! Learn to solve routing problems! Proceedings Article
In: International Conference on Learning Representations, 2019.
2018
Policy Search on Aggregated State Space for Active Sampling Proceedings Article
In: International Symposium on Experimental Robotics, 2018.
BanditSum: Extractive Summarization as a Contextual Bandit Proceedings Article
In: Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 3739–3748, 2018.
Reinforcement Learning with Non-uniform State Representations for Adaptive Search Proceedings Article
In: IEEE International Symposium on Safety, Security, and Rescue Robotics, 2018.
Addressing function approximation error in actor-critic methods Proceedings Article
In: International Conference on Machine Learning, pp. 1587–1596, 2018.
An Inference-Based Policy Gradient Method for Learning Options Proceedings Article
In: International Conference on Machine Learning, pp. 4703-4712, 2018.
Eager and Memory-Based Non-Parametric Stochastic Search Methods for Learning Control Proceedings Article
In: International Conference on Robotics and Automation, 2018.
2017
Non-parametric Policy Search with Limited Information Loss Journal Article
In: Journal of Machine Learning Research, vol. 18, no. 73, pp. 1-46, 2017.
Generalized Exploration in Policy Search Journal Article
In: Machine Learning - Special issue ECML PKDD, vol. 106, no. 9–10, pp. 1705–1724, 2017, ISSN: 1573-0565.
Policy Search with High-Dimensional Context Variables Proceedings Article
In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp. 2632–2638, 2017.
2016
Probabilistic Inference for Determining Options in Reinforcement Learning Journal Article
In: Machine Learning - Special issue ECML PKDD, vol. 104, no. 2–3, pp. 337–357, 2016.
Stable Reinforcement Learning with Auto-Encoders for Tactile and Visual Data Proceedings Article
In: International Conference on Intelligent Robots and Systems, pp. 3928–3934, 2016.
Active Tactile Object Exploration with Gaussian Processes Proceedings Article
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 4925–4930, 2016.
2015
Learning of Non-Parametric Control Policies with High-Dimensional State Features Proceedings Article
In: International Conference on Artificial Intelligence and Statistics, pp. 1004–1012, 2015.
Learning Robot In-Hand Manipulation with Tactile Features Proceedings Article
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2015.
Stabilizing Novel Objects by Learning to Predict Tactile Slip Proceedings Article
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 5065–5072, 2015.
Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks Proceedings Article
In: Proceedings of the International Conference on Robotics and Automation (ICRA), 2015.
2014
Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments Journal Article
In: IEEE Transactions on Robotics (TRo), vol. 5, pp. 1198-1209, 2014.
Learning to Predict Phases of Manipulation Tasks as Hidden States Proceedings Article
In: Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA), 2014.
Policy Search For Learning Robot Control Using Sparse Data Proceedings Article
In: Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA), 2014.
2013
Probabilistic Interactive Segmentation for Anthropomorphic Robots in Cluttered Environments Proceedings Article
In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2013.
2012
Maximally Informative Interaction Learning for Scene Exploration Proceedings Article
In: Proceedings of the International Conference on Robot Systems (IROS), 2012.
2011
Adaptive Visual Face Tracking for an Autonomous Robot Proceedings Article
In: Proceedings of the Belgian-Dutch Artificial Intelligence Conference (BNAIC 11), 2011.
Ph.D. Thesis
2016
Machine Learning through Exploration for Perception-Driven Robotics PhD Thesis
2016.