Daniel Nikovski

Orcid: 0000-0003-2919-645X

According to our database1, Daniel Nikovski authored at least 106 papers between 1992 and 2024.

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Bibliography

2024
Memory-Based Learning of Global Control Policies from Local Controllers.
Proceedings of the 21st International Conference on Informatics in Control, 2024

Memory-Based Global Iterative Linear Quadratic Control.
Proceedings of the 10th International Conference on Control, 2024

Adaptive Velocity Estimators for Learning Control.
Proceedings of the 10th International Conference on Control, 2024

2023
Forward Dynamics Estimation from Data-Driven Inverse Dynamics Learning.
CoRR, 2023

A Decision-Dependent Chance-Constrained Planning Model for Distribution Networks Under Extreme Weather Events.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2023

Constrained Dynamic Movement Primitives for Collision Avoidance in Novel Environments.
IROS, 2023

Stochastic Learning Manipulation of Object Pose With Under-Actuated Impulse Generator Arrays.
Proceedings of the International Conference on Machine Learning and Applications, 2023

Design of Adaptive Compliance Controllers for Safe Robotic Assembly.
Proceedings of the European Control Conference, 2023

Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control.
Proceedings of the European Control Conference, 2023

Model-Based Learning Controller Design for a Furuta Pendulum.
Proceedings of the 9th International Conference on Control, 2023

Estimating traffic density using transformer decoders.
Proceedings of the 14th International Conference on Ambient Systems, 2023

Travel-time prediction using neural-network-based mixture models.
Proceedings of the 14th International Conference on Ambient Systems, 2023

Learning Object Manipulation With Under-Actuated Impulse Generator Arrays.
Proceedings of the American Control Conference, 2023

Learning Control from Raw Position Measurements.
Proceedings of the American Control Conference, 2023

2022
Model-Based Policy Search Using Monte Carlo Gradient Estimation With Real Systems Application.
IEEE Trans. Robotics, 2022

Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills.
CoRR, 2022

Fair Blackout Rotation for Distribution Systems under Extreme Weather Events.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference Europe, 2022

Context-Aware Destination and Time-To-Destination Prediction Using Machine learning.
Proceedings of the IEEE International Smart Cities Conference, 2022

Deep Reinforcement Learning for Optimal Sailing Upwind.
Proceedings of the International Joint Conference on Neural Networks, 2022

Transfer Learning for Bayesian Optimization with Principal Component Analysis.
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Transformer Networks for Predictive Group Elevator Control.
Proceedings of the European Control Conference, 2022

Imitation and Supervised Learning of Compliance for Robotic Assembly.
Proceedings of the European Control Conference, 2022

2021
Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation.
IEEE Robotics Autom. Lett., 2021

Model-based Policy Search for Partially Measurable Systems.
CoRR, 2021

Distribution Fault Location Using Graph Neural Network with Both Node and Link Attributes.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2021

Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models.
Proceedings of the 2021 European Control Conference, 2021

Dynamic Thermal Comfort Optimization for Groups.
Proceedings of the 2021 American Control Conference, 2021

Personalizing Individual Comfort in the Group Setting.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements.
IEEE Robotics Autom. Lett., 2020

Towards Human-Level Learning of Complex Physical Puzzles.
CoRR, 2020

Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks.
CoRR, 2020

A Holistic Framework for Parameter Coordination of Interconnected Microgrids against Disasters.
CoRR, 2020

Multi-label Prediction in Time Series Data using Deep Neural Networks.
CoRR, 2020

CVaR-constrained Stochastic Bidding Strategy for a Virtual Power Plant with Mobile Energy Storages.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2020

Distributed Average Consensus Algorithm for Damage Assessment of Power Distribution System.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2020

Personalized Destination Prediction Using Transformers in a Contextless Data Setting.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Local Policy Optimization for Trajectory-Centric Reinforcement Learning.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Reactive Planning in Dynamic Environments.
Proceedings of the 4th Conference on Robot Learning, 2020

The Missing Input Problem.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Deep Reinforcement Learning for Joint Bidding and Pricing of Load Serving Entity.
IEEE Trans. Smart Grid, 2019

Introducing time series chains: a new primitive for time series data mining.
Knowl. Inf. Syst., 2019

Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control.
CoRR, 2019

Learning Dynamical Demand Response Model in Real-Time Pricing Program.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2019

Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze.
Proceedings of the International Conference on Robotics and Automation, 2019

Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics.
Proceedings of the International Conference on Robotics and Automation, 2019

Fault Detection and Classification of Time Series Using Localized Matrix Profiles.
Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019

Distributed Estimation and Detection of Cyber-Physical Attacks in Power Systems.
Proceedings of the 17th IEEE International Conference on Communications Workshops, 2019

Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models.
Proceedings of the 17th European Control Conference, 2019

2018
Anomaly Detection in Discrete Manufacturing Systems using Event Relationship Tables.
Proceedings of the 29th International Workshop on Principles of Diagnosis co-located with 10th IFAC Symposium on Fault Detection, 2018

Time Series Chains: A Novel Tool for Time Series Data Mining.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Learning to regulate rolling ball motion.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Random Projection Filter Bank for Time Series Data.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Three-level co-optimization model for generation scheduling of integrated energy and regulation market.
Proceedings of the 2017 IEEE Innovative Smart Grid Technologies - Asia, 2017

Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award).
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Deep reinforcement learning for partial differential equation control.
Proceedings of the 2017 American Control Conference, 2017

Value-Aware Loss Function for Model-based Reinforcement Learning.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Submodular Function Maximization for Group Elevator Scheduling.
Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling, 2017

2016
Modeling and Forecasting Self-Similar Power Load Due to EV Fast Chargers.
IEEE Trans. Smart Grid, 2016

Exemplar learning for extremely efficient anomaly detection in real-valued time series.
Data Min. Knowl. Discov., 2016

An IoT system to estimate personal thermal comfort.
Proceedings of the 3rd IEEE World Forum on Internet of Things, 2016

Mitigating substation demand fluctuations using decoupled price schemes for demand response.
Proceedings of the 2016 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2016

Regularized covariance matrix estimation with high dimensional data for supervised anomaly detection problems.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Learning to control partial differential equations: Regularized Fitted Q-Iteration approach.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

A humidity integrated building thermal model.
Proceedings of the 2016 American Control Conference, 2016

Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Barycentric quantization for planning in continuous domains.
AI Commun., 2015

A generalized admittance based method for fault location analysis of distribution systems.
Proceedings of the 2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2015

Electricity theft detection using smart meter data.
Proceedings of the 2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2015

Locating double-line-to-ground faults using hybrid current profile approach.
Proceedings of the 2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2015

Static voltage stability detection using local measurement for microgrids in a power distribution network.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

A framework for real-time near-optimal train run-curve computation with dynamic travel time and speed limits.
Proceedings of the American Control Conference, 2015

2014
Energy-efficient collision-free trajectory planning using Alternating Quadratic Programming.
Proceedings of the American Control Conference, 2014

2013
Smart Meter Data Analysis for Power Theft Detection.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2013

Predicting link travel times from floating car data.
Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems, 2013

Estimating locations of single-phase-to-ground faults of ungrounded distribution systems.
Proceedings of the 4th IEEE PES Innovative Smart Grid Technologies Europe, 2013

Global optimization of multi-period optimal power flow.
Proceedings of the American Control Conference, 2013

2012
Hybrid three-phase load flow method for ungrounded distribution systems.
Proceedings of the 3rd IEEE PES Innovative Smart Grid Technologies Europe, 2012

Matcher Composition Methods for Automatic Schema Matching.
Proceedings of the Enterprise Information Systems - 14th International Conference, 2012

Bayesian Networks for Matcher Composition in Automatic Schema Matching.
Proceedings of the ICEIS 2012 - Proceedings of the 14th International Conference on Enterprise Information Systems, Volume 1, Wroclaw, Poland, 28 June, 2012

Global optimization of Optimal Power Flow using a branch & bound algorithm.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011
Construction of embedded Markov decision processes for optimal control of non-linear systems with continuous state spaces.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Fast adaptive algorithms for abrupt change detection.
Mach. Learn., 2010

2009
Memory-Based Modeling of Seasonality for Prediction of Climatic Time Series.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009

Semi-supervised Information Extraction from Variable-length Web-page Lists.
Proceedings of the ICEIS 2009, 2009

2008
Incremental exemplar learning schemes for classification on embedded devices.
Mach. Learn., 2008

Workflow Trees for Representation and Mining of Implicitly Concurrent Business Processes.
Proceedings of the ICEIS 2008, 2008

2006
Induction of compact decision trees for personalized recommendation.
Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

2004
Exact calculation of expected waiting times for group elevator control.
IEEE Trans. Autom. Control., 2004

Theory and Applied Computing: Observations and Anecdotes.
Proceedings of the Mathematical Foundations of Computer Science 2004, 2004

Optimal Parking in Group Elevator Control.
Proceedings of the 2004 IEEE International Conference on Robotics and Automation, 2004

2003
Marginalizing Out Future Passengers in Group Elevator Control.
Proceedings of the UAI '03, 2003

Decision-Theoretic Group Elevator Scheduling.
Proceedings of the Thirteenth International Conference on Automated Planning and Scheduling (ICAPS 2003), 2003

2002
Learning probabilistic models for optimal visual servo control of dynamic manipulation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland, September 30, 2002

Learning probabilistic models for state tracking of mobile robots.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland, September 30, 2002

2000
Constructing Bayesian Networks for Medical Diagnosis from Incomplete and Partially Correct Statistics.
IEEE Trans. Knowl. Data Eng., 2000

Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Grounding State Representations in Sensory Experience for Reasoning and Planning by Mobile Robots.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1999
Learning discrete Bayesian models for autonomous agent navigation.
Proceedings of the Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation, 1999

1996
Comparison of Two Learning Networks for Time Series Prediction.
Proceedings of the Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 1996

Amelia.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1993
Speech recognition based on Kohonen self-organizing feature maps and hybrid connectionist systems.
Proceedings of the First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, 1993

1992
Prognostic Expert Systems on a Hybrid Connectionist Environment.
Proceedings of the Artificial Intelligence V: Methodology, Systems, Applications, 1992


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