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Daniel Nikolaev Nikovski
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2020 – today
- 2024
[c88]Daniel Nikovski, Junmin Zhong, William Yerazunis:
Memory-Based Global Iterative Linear Quadratic Control. CoDIT 2024: 1056-1061- [c87]Daniel Nikovski, William Yerazunis:
Adaptive Velocity Estimators for Learning Control. CoDIT 2024: 1062-1067 - [c86]Daniel Nikovski, Junmin Zhong, William Yerazunis:
Memory-Based Learning of Global Control Policies from Local Controllers. ICINCO (1) 2024: 237-244 - [c85]Junmin Zhong, Daniel Nikovski, William Yerazunis, T. Ando:
Learning Time-Optimal Control of Gantry Cranes. ICMLA 2024: 945-950 - 2023
- [c84]Chuizheng Kong
, William Yerazunis, Daniel Nikovski:
Learning Object Manipulation With Under-Actuated Impulse Generator Arrays. ACC 2023: 710-717 - [c83]Fabio Amadio, Alberto Dalla Libera, Daniel Nikovski, Ruggero Carli, Diego Romeres:
Learning Control from Raw Position Measurements. ACC 2023: 2171-2178 - [c82]Yinsong Wang, Jing Zhang, Daniel Nikovski, Takuro Kojima:
Estimating traffic density using transformer decoders. ANT/EDI40 2023: 1027-1032 - [c81]Abhishek Sharma, Jing Zhang, Daniel Nikovski, Finale Doshi-Velez:
Travel-time prediction using neural-network-based mixture models. ANT/EDI40 2023: 1033-1038 - [c80]Daniel Nikovski, William Yerazunis, Abraham Goldsmith:
Model-Based Learning Controller Design for a Furuta Pendulum. CoDIT 2023: 764-767 - [c79]Devesh K. Jha, Siddarth Jain, Diego Romeres, William Yerazunis, Daniel Nikovski:
Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control. ECC 2023: 1-8 - [c78]Devesh K. Jha, Diego Romeres, Siddarth Jain, William Yerazunis, Daniel Nikovski:
Design of Adaptive Compliance Controllers for Safe Robotic Assembly. ECC 2023: 1-8 - [c77]Chuizheng Kong, William Yerazunis, Daniel Nikovski:
Stochastic Learning Manipulation of Object Pose With Under-Actuated Impulse Generator Arrays. ICMLA 2023: 112-119 - [c76]Seiji Shaw, Devesh K. Jha, Arvind U. Raghunathan, Radu Corcodel, Diego Romeres, George Konidaris, Daniel Nikovski:
Constrained Dynamic Movement Primitives for Collision Avoidance in Novel Environments. IROS 2023: 3672-3679 - [c75]Anping Zhou, Hongbo Sun, Shoichi Kitamura, Daniel Nikovski:
A Decision-Dependent Chance-Constrained Planning Model for Distribution Networks Under Extreme Weather Events. ISGT EUROPE 2023: 1-5 - [i28]Fabio Amadio, Alberto Dalla Libera, Daniel Nikovski, Ruggero Carli, Diego Romeres:
Learning Control from Raw Position Measurements. CoRR abs/2301.13183 (2023) - [i27]Chuizheng Kong, William Yerazunis, Daniel Nikovski:
Learning Object Manipulation With Under-Actuated Impulse Generator Arrays. CoRR abs/2303.03282 (2023) - [i26]Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli, Daniel Nikovski, Diego Romeres:
Forward Dynamics Estimation from Data-Driven Inverse Dynamics Learning. CoRR abs/2307.05093 (2023) - 2022
- [j12]Fabio Amadio, Alberto Dalla Libera, Riccardo Antonello, Daniel Nikovski, Ruggero Carli, Diego Romeres:
Model-Based Policy Search Using Monte Carlo Gradient Estimation With Real Systems Application. IEEE Trans. Robotics 38(6): 3879-3898 (2022) - [c74]Jing Zhang, Athanasios Tsiligkaridis, Hiroshi Taguchi, Arvind U. Raghunathan, Daniel Nikovski:
Transformer Networks for Predictive Group Elevator Control. ECC 2022: 1429-1435 - [c73]Devesh K. Jha, Diego Romeres, William Yerazunis, Daniel Nikovski:
Imitation and Supervised Learning of Compliance for Robotic Assembly. ECC 2022: 1882-1889 - [c72]Hideyuki Masui, Diego Romeres, Daniel Nikovski:
Transfer Learning for Bayesian Optimization with Principal Component Analysis. ICMLA 2022: 1077-1084 - [c71]Takumi Suda, Daniel Nikovski:
Deep Reinforcement Learning for Optimal Sailing Upwind. IJCNN 2022: 1-8 - [c70]Athanasios Tsiligkaridis, Jing Zhang, Ioannis Ch. Paschalidis, Hiroshi Taguchi, Satoko Sakajo, Daniel Nikovski:
Context-Aware Destination and Time-To-Destination Prediction Using Machine learning. ISC2 2022: 1-7 - [c69]Hongbo Sun, Shoichi Kitamura, Daniel Nikovski:
Fair Blackout Rotation for Distribution Systems under Extreme Weather Events. ISGT-Europe 2022: 1-6 - [i25]Devesh K. Jha, Diego Romeres, Siddarth Jain, William Yerazunis, Daniel Nikovski:
Design of Adaptive Compliance Controllers for Safe Robotic Assembly. CoRR abs/2204.10447 (2022) - [i24]Jing Zhang, Athanasios Tsiligkaridis, Hiroshi Taguchi, Arvind U. Raghunathan, Daniel Nikovski:
Transformer Networks for Predictive Group Elevator Control. CoRR abs/2208.08948 (2022) - [i23]Seiji Shaw, Devesh K. Jha, Arvind U. Raghunathan, Radu Corcodel, Diego Romeres, George Konidaris, Daniel Nikovski:
Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills. CoRR abs/2209.14461 (2022) - [i22]Devesh K. Jha, Siddarth Jain, Diego Romeres, William Yerazunis, Daniel Nikovski:
Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control. CoRR abs/2212.01434 (2022) - 2021
- [j11]Kei Ota, Devesh K. Jha, Diego Romeres, Jeroen van Baar, Kevin A. Smith, Takayuki Semitsu, Tomoaki Oiki, Alan Sullivan, Daniel Nikovski, Joshua B. Tenenbaum:
Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation. IEEE Robotics Autom. Lett. 6(2): 4241-4248 (2021) - [c68]Emil Laftchiev, Diego Romeres, Daniel Nikovski:
Personalizing Individual Comfort in the Group Setting. AAAI 2021: 15339-15346 - [c67]Emil Laftchiev, Diego Romeres, Daniel Nikovski:
Dynamic Thermal Comfort Optimization for Groups. ACC 2021: 1456-1463 - [c66]Alberto Dalla Libera, Fabio Amadio, Daniel Nikovski, Ruggero Carli, Diego Romeres:
Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models. ECC 2021: 243-248 - [c65]Siyuan Dong, Devesh K. Jha, Diego Romeres, Sangwoon Kim, Daniel Nikovski, Alberto Rodriguez:
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry. ICRA 2021: 6437-6443 - [c64]Hongbo Sun, Shunsuke Kawano, Daniel Nikovski, Tomihiro Takano, Kazuyuki Mori:
Distribution Fault Location Using Graph Neural Network with Both Node and Link Attributes. ISGT-Europe 2021: 1-6 - [i21]Fabio Amadio, Alberto Dalla Libera, Ruggero Carli, Daniel Nikovski, Diego Romeres:
Model-based Policy Search for Partially Measurable Systems. CoRR abs/2101.08740 (2021) - [i20]Fabio Amadio, Alberto Dalla Libera, Riccardo Antonello, Daniel Nikovski, Ruggero Carli, Diego Romeres:
Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application. CoRR abs/2101.12115 (2021) - [i19]Siyuan Dong, Devesh K. Jha, Diego Romeres, Sangwoon Kim, Daniel Nikovski, Alberto Rodriguez:
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry. CoRR abs/2104.01167 (2021) - [i18]Alberto Dalla Libera, Fabio Amadio, Daniel Nikovski, Ruggero Carli, Diego Romeres:
Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models. CoRR abs/2104.12854 (2021) - [i17]Devesh K. Jha, Diego Romeres, William Yerazunis, Daniel Nikovski:
Imitation and Supervised Learning of Compliance for Robotic Assembly. CoRR abs/2111.10488 (2021) - 2020
- [j10]Alberto Dalla Libera, Diego Romeres, Devesh K. Jha, Bill Yerazunis, Daniel Nikovski:
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements. IEEE Robotics Autom. Lett. 5(2): 3548-3555 (2020) - [c63]Emil Laftchiev, Qing Yan, Daniel Nikovski:
The Missing Input Problem. IEEE BigData 2020: 1565-1573 - [c62]Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski:
Deep Reactive Planning in Dynamic Environments. CoRL 2020: 1943-1957 - [c61]Kei Ota, Tomoaki Oiki, Devesh K. Jha, Toshisada Mariyama, Daniel Nikovski:
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning? ICML 2020: 7424-7433 - [c60]Patrik Kolaric, Devesh K. Jha, Arvind U. Raghunathan, Frank L. Lewis, Mouhacine Benosman, Diego Romeres, Daniel Nikovski:
Local Policy Optimization for Trajectory-Centric Reinforcement Learning. ICRA 2020: 5094-5100 - [c59]Athanasios Tsiligkaridis, Jing Zhang, Hiroshi Taguchi, Daniel Nikovski:
Personalized Destination Prediction Using Transformers in a Contextless Data Setting. IJCNN 2020: 1-7 - [c58]Shiva Poudel, Hongbo Sun, Daniel Nikovski, Jinyun Zhang:
Distributed Average Consensus Algorithm for Damage Assessment of Power Distribution System. ISGT 2020: 1-5 - [c57]Dongliang Xiao, Hongbo Sun, Daniel Nikovski, Shoichi Kitamura, Kazuyuki Mori, Hiroyuki Hashimoto:
CVaR-constrained Stochastic Bidding Strategy for a Virtual Power Plant with Mobile Energy Storages. ISGT-Europe 2020: 1171-1175 - [i16]Patrik Kolaric, Devesh K. Jha, Arvind U. Raghunathan, Frank L. Lewis, Mouhacine Benosman, Diego Romeres, Daniel Nikovski:
Local Policy Optimization for Trajectory-Centric Reinforcement Learning. CoRR abs/2001.08092 (2020) - [i15]Wenyu Zhang, Devesh K. Jha, Emil Laftchiev, Daniel Nikovski:
Multi-label Prediction in Time Series Data using Deep Neural Networks. CoRR abs/2001.10098 (2020) - [i14]Alberto Dalla Libera, Diego Romeres, Devesh K. Jha, Bill Yerazunis, Daniel Nikovski:
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements. CoRR abs/2002.10621 (2020) - [i13]Kei Ota, Tomoaki Oiki, Devesh K. Jha, Toshisada Mariyama, Daniel Nikovski:
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning? CoRR abs/2003.01629 (2020) - [i12]Tong Huang, Hongbo Sun, Kyeong Jin Kim, Daniel Nikovski, Le Xie:
A Holistic Framework for Parameter Coordination of Interconnected Microgrids against Disasters. CoRR abs/2006.13840 (2020) - [i11]Yifang Liu, Diego Romeres, Devesh K. Jha, Daniel Nikovski:
Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks. CoRR abs/2007.11646 (2020) - [i10]Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski:
Deep Reactive Planning in Dynamic Environments. CoRR abs/2011.00155 (2020) - [i9]Kei Ota, Devesh K. Jha, Diego Romeres, Jeroen van Baar, Kevin A. Smith, Takayuki Semitsu, Tomoaki Oiki, Alan Sullivan, Daniel Nikovski, Joshua B. Tenenbaum:
Towards Human-Level Learning of Complex Physical Puzzles. CoRR abs/2011.07193 (2020)
2010 – 2019
- 2019
- [j9]Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh:
Introducing time series chains: a new primitive for time series data mining. Knowl. Inf. Syst. 60(2): 1135-1161 (2019) - [j8]Hanchen Xu, Hongbo Sun, Daniel Nikovski, Shoichi Kitamura, Kazuyuki Mori, Hiroyuki Hashimoto:
Deep Reinforcement Learning for Joint Bidding and Pricing of Load Serving Entity. IEEE Trans. Smart Grid 10(6): 6366-6375 (2019) - [c56]Diego Romeres, Devesh K. Jha, William Yerazunis, Daniel Nikovski, Hoang Anh Dau:
Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models. ECC 2019: 1017-1022 - [c55]Ariana Minot, Hongbo Sun, Daniel Nikovski, Jinyun Zhang:
Distributed Estimation and Detection of Cyber-Physical Attacks in Power Systems. ICC Workshops 2019: 1-6 - [c54]Jing Zhang, Daniel Nikovski, Teng-Yok Lee, Tomoya Fujino:
Fault Detection and Classification of Time Series Using Localized Matrix Profiles. ICPHM 2019: 1-7 - [c53]Diego Romeres, Devesh K. Jha, Alberto Dalla Libera, Bill Yerazunis, Daniel Nikovski:
Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze. ICRA 2019: 3195-3202 - [c52]Jeroen van Baar, Alan Sullivan, Radu Cordorel, Devesh K. Jha, Diego Romeres, Daniel Nikovski:
Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics. ICRA 2019: 6001-6007 - [c51]Kei Ota, Devesh K. Jha, Tomoaki Oiki, Mamoru Miura, Takashi Nammoto, Daniel Nikovski, Toshisada Mariyama:
Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning. IROS 2019: 3487-3494 - [c50]Hanchen Xu, Hongbo Sun, Daniel Nikovski, Shoichi Kitamura, Kazuyuki Mori:
Learning Dynamical Demand Response Model in Real-Time Pricing Program. ISGT 2019: 1-5 - [i8]Kei Ota, Devesh K. Jha, Tomoaki Oiki, Mamoru Miura, Takashi Nammoto, Daniel Nikovski, Toshisada Mariyama:
Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning. CoRR abs/1903.05751 (2019) - [i7]Jonathan Chang, Nishanth Kumar, Sean Hastings, Aaron Gokaslan, Diego Romeres, Devesh K. Jha, Daniel Nikovski, George Dimitri Konidaris, Stefanie Tellex:
Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control. CoRR abs/1910.10628 (2019) - 2018
- [c49]Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski:
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. ICML 2018: 3983-3992 - [c48]Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh:
Time Series Chains: A Novel Tool for Time Series Data Mining. IJCAI 2018: 5414-5418 - [c47]Emil Laftchiev, Xinmaio Sun, Hoang Anh Dau, Daniel Nikovski:
Anomaly Detection in Discrete Manufacturing Systems using Event Relationship Tables. DX 2018 - [i6]Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski:
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. CoRR abs/1806.06931 (2018) - [i5]Jeroen van Baar, Alan Sullivan, Radu Cordorel, Devesh K. Jha, Diego Romeres, Daniel Nikovski:
Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics. CoRR abs/1809.04720 (2018) - [i4]Diego Romeres, Devesh K. Jha, Alberto Dalla Libera, William Yerazunis, Daniel Nikovski:
Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze. CoRR abs/1809.04993 (2018) - [i3]Hanchen Xu, Hongbo Sun, Daniel Nikovski, Shoichi Kitamura, Kazuyuki Mori:
Learning Dynamical Demand Response Model in Real-Time Pricing Program. CoRR abs/1812.09567 (2018) - 2017
- [c46]Srikumar Ramalingam, Arvind U. Raghunathan, Daniel Nikovski:
Submodular Function Maximization for Group Elevator Scheduling. ICAPS 2017: 233-241 - [c45]Amir Massoud Farahmand, André Barreto, Daniel Nikovski:
Value-Aware Loss Function for Model-based Reinforcement Learning. AISTATS 2017: 1486-1494 - [c44]Amir-massoud Farahmand, Saleh Nabi, Daniel Nikolaev Nikovski:
Deep reinforcement learning for partial differential equation control. ACC 2017: 3120-3127 - [c43]Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh:
Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award). ICDM 2017: 695-704 - [c42]Hongbo Sun, Yusuke Takaguchi, Daniel Nikovski, Hiroyuki Hashimoto:
Three-level co-optimization model for generation scheduling of integrated energy and regulation market. ISGT Asia 2017: 1-6 - [c41]Amir-massoud Farahmand, Sepideh Pourazarm, Daniel Nikovski:
Random Projection Filter Bank for Time Series Data. NIPS 2017: 6562-6572 - [c40]Devesh K. Jha, Daniel Nikovski, William Yerazunis, Amir-massoud Farahmand:
Learning to regulate rolling ball motion. SSCI 2017: 1-6 - [i2]Srikumar Ramalingam, Arvind U. Raghunathan, Daniel Nikovski:
Submodular Function Maximization for Group Elevator Scheduling. CoRR abs/1707.00617 (2017) - 2016
- [j7]Michael Jones, Daniel Nikovski, Makoto Imamura, Takahisa Hirata:
Exemplar learning for extremely efficient anomaly detection in real-valued time series. Data Min. Knowl. Discov. 30(6): 1427-1454 (2016) - [j6]Nikita Korolko, Zafer Sahinoglu, Daniel Nikovski:
Modeling and Forecasting Self-Similar Power Load Due to EV Fast Chargers. IEEE Trans. Smart Grid 7(3): 1620-1629 (2016) - [c39]Amir-massoud Farahmand, Daniel Nikolaev Nikovski, Yuji Igarashi, Hiroki Konaka:
Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value. AAAI 2016: 3123-3129 - [c38]Jingyang Xu, Daniel Nikovski:
A humidity integrated building thermal model. ACC 2016: 1492-1499 - [c37]Amir-massoud Farahmand, Saleh Nabi, Piyush Grover, Daniel Nikovski:
Learning to control partial differential equations: Regularized Fitted Q-Iteration approach. CDC 2016: 4578-4585 - [c36]Daniel Nikovski, Kiran Byadarhaly:
Regularized covariance matrix estimation with high dimensional data for supervised anomaly detection problems. IJCNN 2016: 2811-2818 - [c35]Hongbo Sun, Ariana Minot, Daniel Nikovski, Hiroyuki Hashimoto, Tomihiro Takano, Yusuke Takaguchi:
Mitigating substation demand fluctuations using decoupled price schemes for demand response. ISGT 2016: 1-5 - [c34]Emil Laftchiev, Daniel Nikovski:
An IoT system to estimate personal thermal comfort. WF-IoT 2016: 672-677 - 2015
- [j5]Daniel Nikolaev Nikovski:
Barycentric quantization for planning in continuous domains. AI Commun. 28(3): 539-551 (2015) - [c33]Jingyang Xu, Daniel Nikovski, Sae Kimura:
A framework for real-time near-optimal train run-curve computation with dynamic travel time and speed limits. ACC 2015: 533-540 - [c32]Zhao Wang, Hongbo Sun, Daniel Nikovski:
Static voltage stability detection using local measurement for microgrids in a power distribution network. CDC 2015: 3254-3259 - [c31]Anamika Dubey, Hongbo Sun, Daniel Nikovski, Tomihiro Takano, Yasuhiro Kojima, Tetsufumi Ohno:
Locating double-line-to-ground faults using hybrid current profile approach. ISGT 2015: 1-5 - [c30]Sanujit Sahoo, Daniel Nikovski, Toru Muso, Kaoru Tsuru:
Electricity theft detection using smart meter data. ISGT 2015: 1-5 - [c29]Zhenyu Tan, Hongbo Sun, Daniel Nikovski, Tomihiro Takano, Yasuhiro Kojima, Tetsufumi Ohno:
A generalized admittance based method for fault location analysis of distribution systems. ISGT 2015: 1-5 - 2014
- [c28]Yiming Zhao, Yebin Wang, Scott A. Bortoff, Daniel Nikovski:
Energy-efficient collision-free trajectory planning using Alternating Quadratic Programming. ACC 2014: 1249-1254 - 2013
- [c27]Ajit Gopalakrishnan, Arvind U. Raghunathan, Daniel Nikovski, Lorenz T. Biegler:
Global optimization of multi-period optimal power flow. ACC 2013: 1157-1164 - [c26]Hongbo Sun, Daniel Nikovski, Tomihiro Takano, Yasuhiro Kojima, Tetsufumi Ohno:
Estimating locations of single-phase-to-ground faults of ungrounded distribution systems. ISGT Europe 2013: 1-5 - [c25]Michael Jones, Yanfeng Geng, Daniel Nikovski, Takahisa Hirata:
Predicting link travel times from floating car data. ITSC 2013: 1756-1763 - [c24]Daniel Nikolaev Nikovski, Zhenhua Wang, Alan Esenther, Hongbo Sun, Keisuke Sugiura, Toru Muso, Kaoru Tsuru:
Smart Meter Data Analysis for Power Theft Detection. MLDM 2013: 379-389 - 2012
- [c23]Ajit Gopalakrishnan, Arvind U. Raghunathan, Daniel Nikovski, Lorenz T. Biegler:
Global optimization of Optimal Power Flow using a branch & bound algorithm. Allerton Conference 2012: 609-616 - [c22]Daniel Nikovski, Alan Esenther, Xiang Ye, Mitsuteru Shiba, Shigenobu Takayama:
Bayesian Networks for Matcher Composition in Automatic Schema Matching. ICEIS (1) 2012: 48-55 - [c21]Daniel Nikovski, Alan Esenther, Xiang Ye, Mitsuteru Shiba, Shigenobu Takayama:
Matcher Composition Methods for Automatic Schema Matching. ICEIS 2012: 108-123 - [c20]Hongbo Sun, Daniel Nikovski, Tetsufumi Ohno, Tomihiro Takano, Yasuhiro Kojima:
Hybrid three-phase load flow method for ungrounded distribution systems. ISGT Europe 2012: 1-8 - [i1]Daniel Nikovski, Matthew Brand:
Marginalizing Out Future Passengers in Group Elevator Control. CoRR abs/1212.2499 (2012) - 2011
- [c19]Daniel Nikovski, Alan Esenther:
Construction of embedded Markov decision processes for optimal control of non-linear systems with continuous state spaces. CDC/ECC 2011: 7944-7949 - 2010
- [j4]Daniel Nikovski, Ankur Jain:
Fast adaptive algorithms for abrupt change detection. Mach. Learn. 79(3): 283-306 (2010)
2000 – 2009
- 2009
- [c18]Daniel Nikovski, Alan Esenther, Akihiro Baba:
Semi-supervised Information Extraction from Variable-length Web-page Lists. ICEIS (1) 2009: 261-266 - [c17]Daniel Nikovski, Ganesan Ramachandran:
Memory-Based Modeling of Seasonality for Prediction of Climatic Time Series. MLDM 2009: 734-748 - 2008
- [j3]Ankur Jain, Daniel Nikovski:
Incremental exemplar learning schemes for classification on embedded devices. Mach. Learn. 72(3): 189-203 (2008) - [c16]Daniel Nikovski:
Workflow Trees for Representation and Mining of Implicitly Concurrent Business Processes. ICEIS (3-2) 2008: 30-36 - [c15]Ankur Jain, Daniel Nikovski:
Incremental Exemplar Learning Schemes for Classification on Embedded Devices. ECML/PKDD (1) 2008: 11 - 2006
- [c14]Daniel Nikovski, Veselin Kulev:
Induction of compact decision trees for personalized recommendation. SAC 2006: 575-581 - 2004
- [j2]Daniel Nikovski, Matthew Brand:
Exact calculation of expected waiting times for group elevator control. IEEE Trans. Autom. Control. 49(10): 1820-1823 (2004) - [c13]Matthew Brand, Daniel Nikovski:
Optimal Parking in Group Elevator Control. ICRA 2004: 1002-1008 - [c12]Matthew Brand, Sarah F. Frisken Gibson, Neal Lesh, Joe Marks, Daniel Nikovski, Ronald N. Perry, Jonathan S. Yedidia:
Theory and Applied Computing: Observations and Anecdotes. MFCS 2004: 106-118 - 2003
- [c11]Daniel Nikovski, Matthew Brand:
Decision-Theoretic Group Elevator Scheduling. ICAPS 2003: 133-142 - [c10]Daniel Nikovski, Matthew Brand:
Marginalizing Out Future Passengers in Group Elevator Control. UAI 2003: 443-450 - 2002
- [c9]Daniel Nikovski, Illah R. Nourbakhsh:
Learning probabilistic models for state tracking of mobile robots. IROS 2002: 1026-1031 - [c8]Daniel Nikovski, Illah R. Nourbakhsh:
Learning probabilistic models for optimal visual servo control of dynamic manipulation. IROS 2002: 1068-1073 - 2000
- [j1]Daniel Nikovski:
Constructing Bayesian Networks for Medical Diagnosis from Incomplete and Partially Correct Statistics. IEEE Trans. Knowl. Data Eng. 12(4): 509-516 (2000) - [c7]Daniel Nikovski:
Grounding State Representations in Sensory Experience for Reasoning and Planning by Mobile Robots. AAAI/IAAI 2000: 1108 - [c6]Daniel Nikovski, Illah R. Nourbakhsh:
Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots. ICML 2000: 671-678
1990 – 1999
- 1999
- [c5]Daniel Nikovski, Illah R. Nourbakhsh:
Learning discrete Bayesian models for autonomous agent navigation. CIRA 1999: 137-143 - 1996
- [c4]Reid G. Simmons, Sebastian Thrun, Greg Armstrong, Richard Goodwin, Karen Zita Haigh, Sven Koenig, Shyjan Mahamud, Daniel Nikovski, Joseph O'Sullivan:
Amelia. AAAI/IAAI, Vol. 2 1996: 1358 - [c3]Daniel Nikovski, Mehdi Zargham:
Comparison of Two Learning Networks for Time Series Prediction. IEA/AIE 1996: 531-536 - 1993
- [c2]Nikola K. Kasabov, Daniel Nikovski, Emilian Peev:
Speech recognition based on Kohonen self-organizing feature maps and hybrid connectionist systems. ANNES 1993: 113-117 - 1992
- [c1]Nikola K. Kasabov, Daniel Nikovski:
Prognostic Expert Systems on a Hybrid Connectionist Environment. AIMSA 1992: 141-148
Coauthor Index
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