Joni Pajarinen

Orcid: 0000-0003-4469-8191

According to our database1, Joni Pajarinen authored at least 88 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning.
IEEE Trans. Pattern Anal. Mach. Intell., November, 2024

Autonomous underwater vehicle link alignment control in unknown environments using reinforcement learning.
J. Field Robotics, September, 2024

A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search.
J. Artif. Intell. Res., 2024

Bi-Level Motion Imitation for Humanoid Robots.
CoRR, 2024

Multi-Scale Fusion for Object Representation.
CoRR, 2024

Organized Grouped Discrete Representation for Object-Centric Learning.
CoRR, 2024

DeMoBot: Deformable Mobile Manipulation with Vision-based Sub-goal Retrieval.
CoRR, 2024

RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands.
CoRR, 2024

Grouped Discrete Representation Guides Object-Centric Learning.
CoRR, 2024

iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning.
CoRR, 2024

AgentMixer: Multi-Agent Correlated Policy Factorization.
CoRR, 2024

ROER: Regularized Optimal Experience Replay.
RLJ, 2024

Cycle Count Estimation of VLIW Processors Using Machine Learning.
Proceedings of the 2024 IEEE Nordic Circuits and Systems Conference (NorCAS), 2024

Residual learning and context encoding for adaptive offline-to-online reinforcement learning.
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Optimistic Multi-Agent Policy Gradient.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Function-space Parameterization of Neural Networks for Sequential Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Continuous Monte Carlo Graph Search.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Backpropagation Through Agents.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning-Based Propulsion Control for Amphibious Quadruped Robots With Dynamic Adaptation to Changing Environment.
IEEE Robotics Autom. Lett., December, 2023

POMDP Planning Under Object Composition Uncertainty: Application to Robotic Manipulation.
IEEE Trans. Robotics, February, 2023

Partially Observable Markov Decision Processes in Robotics: A Survey.
IEEE Trans. Robotics, February, 2023

Optimistic Multi-Agent Policy Gradient for Cooperative Tasks.
CoRR, 2023

Less Is More: Robust Robot Learning via Partially Observable Multi-Agent Reinforcement Learning.
CoRR, 2023

Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning.
CoRR, 2023

Monte-Carlo tree search with uncertainty propagation via optimal transport.
CoRR, 2023

Sparse Function-space Representation of Neural Networks.
CoRR, 2023

Towards Energy Efficient Control for Commercial Heavy-Duty Mobile Cranes: Modeling Hydraulic Pressures using Machine Learning.
CoRR, 2023

Swapped goal-conditioned offline reinforcement learning.
CoRR, 2023

Prioritized offline Goal-swapping Experience Replay.
CoRR, 2023

Hybrid Search for Efficient Planning with Completeness Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Suicidal Pedestrian: Generation of Safety-Critical Scenarios for Autonomous Vehicles.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Seq2Seq Imitation Learning for Tactile Feedback-based Manipulation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Simplified Temporal Consistency Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Hierarchical Imitation Learning with Vector Quantized Models.
Proceedings of the International Conference on Machine Learning, 2023

State-Conditioned Adversarial Subgoal Generation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Nonlinear Model Learning for Compensation and Feedforward Control of Real-World Hydraulic Actuators Using Gaussian Processes.
IEEE Robotics Autom. Lett., 2022

Monte-Carlo Robot Path Planning.
IEEE Robotics Autom. Lett., 2022

Visual Rewards From Observation for Sequential Tasks: Autonomous Pile Loading.
Frontiers Robotics AI, 2022

Continuous Monte Carlo Graph Search.
CoRR, 2022

Self-Paced Multi-Agent Reinforcement Learning.
CoRR, 2022

Hierarchical Reinforcement Learning with Adversarially Guided Subgoals.
CoRR, 2022

Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning.
Algorithms, 2022

Redeeming intrinsic rewards via constrained optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GPU-Accelerated Policy Optimization via Batch Automatic Differentiation of Gaussian Processes for Real-World Control.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Curriculum Reinforcement Learning via Constrained Optimal Transport.
Proceedings of the International Conference on Machine Learning, 2022

Boosted Curriculum Reinforcement Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Topological Experience Replay.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning.
J. Mach. Learn. Res., 2021

Reinforcement Learning using Guided Observability.
CoRR, 2021

Machine Learning Based Mobile Network Throughput Classification.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2021

Neural Network Controller for Autonomous Pile Loading Revised.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Convex Regularization in Monte-Carlo Tree Search.
Proceedings of the 38th International Conference on Machine Learning, 2021

Latent Derivative Bayesian Last Layer Networks.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Probabilistic Approach to Physical Object Disentangling.
IEEE Robotics Autom. Lett., 2020

Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization.
IEEE Robotics Autom. Lett., 2020

POMDP Manipulation Planning under Object Composition Uncertainty.
CoRR, 2020

Technical Report: The Policy Graph Improvement Algorithm.
CoRR, 2020

Multi-agent active information gathering in discrete and continuous-state decentralized POMDPs by policy graph improvement.
Auton. Agents Multi Agent Syst., 2020

Self-Paced Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep Adversarial Reinforcement Learning for Object Disentangling.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Generalized Mean Estimation in Monte-Carlo Tree Search.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Learning Intention Aware Online Adaptation of Movement Primitives.
IEEE Robotics Autom. Lett., 2019

Compatible natural gradient policy search.
Mach. Learn., 2019

Model-based Lookahead Reinforcement Learning.
CoRR, 2019

Exploration Driven by an Optimistic Bellman Equation.
Proceedings of the International Joint Conference on Neural Networks, 2019

Projections for Approximate Policy Iteration Algorithms.
Proceedings of the 36th International Conference on Machine Learning, 2019

Information Gathering in Decentralized POMDPs by Policy Graph Improvement.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
An Algorithmic Perspective on Imitation Learning.
Found. Trends Robotics, 2018

Utilizing Human Feedback in POMDP Execution and Specification.
Proceedings of the 18th IEEE-RAS International Conference on Humanoid Robots, 2018

2017
Robotic manipulation of multiple objects as a POMDP.
Artif. Intell., 2017

Hybrid control trajectory optimization under uncertainty.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

2016
Benchmarking RGB-D Segmentation: Toy Dataset of Complex Crowded Scenes.
Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016), 2016

Learning in-contact control strategies from demonstration.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Sparse Latent Space Policy Search.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Decision making under uncertain segmentations.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014
Optimizing Spatial and Temporal Reuse inWireless Networks by Decentralized Partially Observable Markov Decision Processes.
IEEE Trans. Mob. Comput., 2014

Robotic manipulation in object composition space.
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

Real-time recognition of pointing gestures for robot to robot interaction.
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

2013
Planning under uncertainty for large-scale problems with applications to wireless networking ; Päätöksenteko epävarmuuden vallitessa suurissa ongelmissa ja sovelluksia langattomaan tiedonsiirtoon.
PhD thesis, 2013

Expectation Maximization for Average Reward Decentralized POMDPs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

2011
Fault tolerant machine learning for nanoscale cognitive radio.
Neurocomputing, 2011

Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Efficient Planning for Factored Infinite-Horizon DEC-POMDPs.
Proceedings of the IJCAI 2011, 2011

2010
Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009
Latent state models of primary user behavior for opportunistic spectrum access.
Proceedings of the IEEE 20th International Symposium on Personal, 2009


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