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Danil V. Prokhorov
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Publications
- 2024
- [i20]Navid Hashemi, Bardh Hoxha, Danil V. Prokhorov, Georgios Fainekos, Jyotirmoy Deshmukh:
Scaling Learning based Policy Optimization for Temporal Tasks via Dropout. CoRR abs/2403.15826 (2024) - 2023
- [c73]Kandai Watanabe, Georgios Fainekos, Bardh Hoxha, Morteza Lahijanian, Danil V. Prokhorov, Sriram Sankaranarayanan, Tomoya Yamaguchi:
Timed Partial Order Inference Algorithm. ICAPS 2023: 639-647 - [c72]Navid Hashemi, Xin Qin, Jyotirmoy V. Deshmukh, Georgios Fainekos, Bardh Hoxha, Danil V. Prokhorov, Tomoya Yamaguchi:
Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives. ACC 2023: 4096-4103 - [c71]Hoang-Dung Tran, Sungwoo Choi, Hideki Okamoto, Bardh Hoxha, Georgios Fainekos, Danil V. Prokhorov:
Quantitative Verification for Neural Networks using ProbStars. HSCC 2023: 4:1-4:12 - [c70]Hoang-Dung Tran, Sung Woo Choi, Xiaodong Yang, Tomoya Yamaguchi, Bardh Hoxha, Danil V. Prokhorov:
Verification of Recurrent Neural Networks with Star Reachability. HSCC 2023: 6:1-6:13 - [c69]Navid Hashemi, Bardh Hoxha, Tomoya Yamaguchi, Danil V. Prokhorov, Georgios Fainekos, Jyotirmoy Deshmukh:
A Neurosymbolic Approach to the Verification of Temporal Logic Properties of Learning-enabled Control Systems. ICCPS 2023: 98-109 - [c68]Mitchell Black, Georgios Fainekos, Bardh Hoxha, Danil V. Prokhorov, Dimitra Panagou:
Safety Under Uncertainty: Tight Bounds with Risk-Aware Control Barrier Functions. ICRA 2023: 12686-12692 - [c66]Jacob Anderson, Georgios Fainekos, Bardh Hoxha, Hideki Okamoto, Danil V. Prokhorov:
Pattern Matching for Perception Streams. RV 2023: 251-270 - [i19]Kandai Watanabe, Bardh Hoxha, Danil V. Prokhorov, Georgios Fainekos, Morteza Lahijanian, Sriram Sankaranarayanan, Tomoya Yamaguchi:
Timed Partial Order Inference Algorithm. CoRR abs/2302.02501 (2023) - [i18]Navid Hashemi, Bardh Hoxha, Tomoya Yamaguchi, Danil V. Prokhorov, Georgios Fainekos, Jyotirmoy Deshmukh:
A Neurosymbolic Approach to the Verification of Temporal Logic Properties of Learning enabled Control Systems. CoRR abs/2303.05394 (2023) - [i17]Mitchell Black, Georgios Fainekos, Bardh Hoxha, Danil V. Prokhorov, Dimitra Panagou:
Safety Under Uncertainty: Tight Bounds with Risk-Aware Control Barrier Functions. CoRR abs/2304.01040 (2023) - [i16]Alexander Bastounis, Alexander N. Gorban, Anders C. Hansen, Desmond J. Higham, Danil V. Prokhorov, Oliver J. Sutton, Ivan Yu. Tyukin, Qinghua Zhou:
The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning. CoRR abs/2309.07072 (2023) - [i15]Hardik Parwana, Mitchell Black, Bardh Hoxha, Hideki Okamoto, Georgios Fainekos, Danil V. Prokhorov, Dimitra Panagou:
Feasible Space Monitoring for Multiple Control Barrier Functions with application to Large Scale Indoor Navigation. CoRR abs/2312.07803 (2023) - 2022
- [c65]Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran, Bardh Hoxha, Taylor T. Johnson, Danil V. Prokhorov:
Neural Network Repair with Reachability Analysis. FORMATS 2022: 221-236 - [i14]Navid Hashemi, Xin Qin, Jyotirmoy V. Deshmukh, Georgios Fainekos, Bardh Hoxha, Danil V. Prokhorov, Tomoya Yamaguchi:
Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives. CoRR abs/2210.07439 (2022) - 2021
- [j50]Shakiba Yaghoubi, Keyvan Majd, Georgios Fainekos, Tomoya Yamaguchi, Danil V. Prokhorov, Bardh Hoxha:
Risk-Bounded Control Using Stochastic Barrier Functions. IEEE Control. Syst. Lett. 5(5): 1831-1836 (2021) - [c64]Shakiba Yaghoubi, Keyvan Majd, Georgios Fainekos, Tomoya Yamaguchi, Danil V. Prokhorov, Bardh Hoxha:
Risk-bounded Control using Stochastic Barrier Functions. ACC 2021: 1131-1136 - [c63]Shakiba Yaghoubi, Georgios Fainekos, Tomoya Yamaguchi, Danil V. Prokhorov, Bardh Hoxha:
Risk-Bounded Control with Kalman Filtering and Stochastic Barrier Functions. CDC 2021: 5213-5219 - [c62]Xiaodong Yang, Taylor T. Johnson, Hoang-Dung Tran, Tomoya Yamaguchi, Bardh Hoxha, Danil V. Prokhorov:
Reachability analysis of deep ReLU neural networks using facet-vertex incidence. HSCC 2021: 18:1-18:7 - [c61]Keyvan Majd, Shakiba Yaghoubi, Tomoya Yamaguchi, Bardh Hoxha, Danil V. Prokhorov, Georgios Fainekos:
Safe Navigation in Human Occupied Environments Using Sampling and Control Barrier Functions. IROS 2021: 5794-5800 - [i12]Keyvan Majd, Shakiba Yaghoubi, Tomoya Yamaguchi, Bardh Hoxha, Danil V. Prokhorov, Georgios Fainekos:
Safe Navigation in Human Occupied Environments Using Sampling and Control Barrier Functions. CoRR abs/2105.01204 (2021) - [i11]Xiaodong Yang, Tomoya Yamaguchi, Hoang-Dung Tran, Bardh Hoxha, Taylor T. Johnson, Danil V. Prokhorov:
Reachability Analysis of Convolutional Neural Networks. CoRR abs/2106.12074 (2021) - [i10]Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran, Bardh Hoxha, Taylor T. Johnson, Danil V. Prokhorov:
Neural Network Repair with Reachability Analysis. CoRR abs/2108.04214 (2021) - [i9]Shakiba Yaghoubi, Georgios Fainekos, Tomoya Yamaguchi, Danil V. Prokhorov, Bardh Hoxha:
Risk-Bounded Control with Kalman Filtering and Stochastic Barrier Functions. CoRR abs/2112.14912 (2021) - 2020
- [j48]Fan Yang, Lei Zhang, Sijia Yu, Danil V. Prokhorov, Xue Mei, Haibin Ling:
Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection. IEEE Trans. Intell. Transp. Syst. 21(4): 1525-1535 (2020) - [j46]Cumhur Erkan Tuncali, Georgios Fainekos, Danil V. Prokhorov, Hisahiro Ito, James Kapinski:
Requirements-Driven Test Generation for Autonomous Vehicles With Machine Learning Components. IEEE Trans. Intell. Veh. 5(2): 265-280 (2020) - [c60]Yuji Date, Takeshi Baba, Bardh Hoxha, Tomoya Yamaguchi, Danil V. Prokhorov:
Application of Simulation-Based Methods on Autonomous Vehicle Control with Deep Neural Network: Work-in-Progress. EMSOFT 2020: 1-3 - [c59]Tomoya Yamaguchi, Bardh Hoxha, Danil V. Prokhorov, Jyotirmoy V. Deshmukh:
Specification-guided Software Fault Localization for Autonomous Mobile Systems. MEMOCODE 2020: 1-12 - 2019
- [j45]Ivan Yu. Tyukin, Alexander N. Gorban, Stephen Green, Danil V. Prokhorov:
Fast construction of correcting ensembles for legacy Artificial Intelligence systems: Algorithms and a case study. Inf. Sci. 485: 230-247 (2019) - [j44]Jifeng Shen, Xin Zuo, Wankou Yang, Danil V. Prokhorov, Xue Mei, Haibin Ling:
Differential Features for Pedestrian Detection: A Taylor Series Perspective. IEEE Trans. Intell. Transp. Syst. 20(8): 2913-2922 (2019) - [j43]Tomoki Nishi, Prashant Doshi, Danil V. Prokhorov:
Merging in Congested Freeway Traffic Using Multipolicy Decision Making and Passive Actor-Critic Learning. IEEE Trans. Intell. Veh. 4(2): 287-297 (2019) - [j42]Wangmeng Zuo, Xi Peng, Ling Shao, Danil V. Prokhorov, Horst Bischof:
Guest Editorial Special Issue on Discriminative Learning for Model Optimization and Statistical Inference. IEEE Trans. Neural Networks Learn. Syst. 30(10): 2894-2897 (2019) - [j41]Zhiqiang Wan, Hepeng Li, Haibo He, Danil V. Prokhorov:
Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning. IEEE Trans. Smart Grid 10(5): 5246-5257 (2019) - [c58]Jyotirmoy V. Deshmukh, James Kapinski, Tomoya Yamaguchi, Danil V. Prokhorov:
Learning Deep Neural Network Controllers for Dynamical Systems with Safety Guarantees: Invited Paper. ICCAD 2019: 1-7 - [i8]Fan Yang, Lei Zhang, Sijia Yu, Danil V. Prokhorov, Xue Mei, Haibin Ling:
Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection. CoRR abs/1901.06340 (2019) - [i7]Cumhur Erkan Tuncali, Georgios Fainekos, Danil V. Prokhorov, Hisahiro Ito, James Kapinski:
Requirements-driven Test Generation for Autonomous Vehicles with Machine Learning Components. CoRR abs/1908.01094 (2019) - 2018
- [j40]Shuai Di, Honggang Zhang, Chun-Guang Li, Xue Mei, Danil V. Prokhorov, Haibin Ling:
Cross-Domain Traffic Scene Understanding: A Dense Correspondence-Based Transfer Learning Approach. IEEE Trans. Intell. Transp. Syst. 19(3): 745-757 (2018) - [j39]Heng Fan, Xue Mei, Danil V. Prokhorov, Haibin Ling:
Multi-Level Contextual RNNs With Attention Model for Scene Labeling. IEEE Trans. Intell. Transp. Syst. 19(11): 3475-3485 (2018) - [c56]He Jiang, Xiao-Kang Liu, Haibo He, Chengzhi Yuan, Danil V. Prokhorov:
Neural Network Based Distributed Consensus Control for Heterogeneous Multi-agent Systems. ACC 2018: 5175-5180 - [c55]Ivan Yu. Tyukin, Alexander N. Gorban, Danil V. Prokhorov, Stephen Green:
Efficiency of Shallow Cascades for Improving Deep Learning AI Systems. IJCNN 2018: 1-8 - [i6]Ivan Yu. Tyukin, Alexander N. Gorban, Stephen Green, Danil V. Prokhorov:
Fast Construction of Correcting Ensembles for Legacy Artificial Intelligence Systems: Algorithms and a Case Study. CoRR abs/1810.05593 (2018) - 2017
- [j38]Yong-Duan Song, Frank L. Lewis, Marios M. Polycarpou, Danil V. Prokhorov, Dongbin Zhao:
Guest Editorial Special Issue on New Developments in Neural Network Structures for Signal Processing, Autonomous Decision, and Adaptive Control. IEEE Trans. Neural Networks Learn. Syst. 28(3): 494-499 (2017) - [j37]Jun Li, Xue Mei, Danil V. Prokhorov, Dacheng Tao:
Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene. IEEE Trans. Neural Networks Learn. Syst. 28(3): 690-703 (2017) - [c54]Heng Fan, Xue Mei, Danil V. Prokhorov, Haibin Ling:
RGB-D Scene Labeling with Multimodal Recurrent Neural Networks. CVPR Workshops 2017: 203-211 - [c53]Han-Kai Hsu, Yi-Hsuan Tsai, Xue Mei, Kuan-Hui Lee, Naoki Nagasaka, Danil V. Prokhorov, Ming-Hsuan Yang:
Learning to tell brake and turn signals in videos using CNN-LSTM structure. ITSC 2017: 1-6 - [i5]Tomoki Nishi, Prashant Doshi, Michael R. James, Danil V. Prokhorov:
Actor-Critic for Linearly-Solvable Continuous MDP with Partially Known Dynamics. CoRR abs/1706.01077 (2017) - [i4]Tomoki Nishi, Prashant Doshi, Danil V. Prokhorov:
Freeway Merging in Congested Traffic based on Multipolicy Decision Making with Passive Actor Critic. CoRR abs/1707.04489 (2017) - 2016
- [j36]Alexander N. Gorban, Ivan Yu. Tyukin, Danil V. Prokhorov, Konstantin I. Sofeikov:
Approximation with random bases: Pro et Contra. Inf. Sci. 364-365: 129-145 (2016) - [j35]Danil V. Prokhorov, Sadayuki Tsugawa, Christoph Stiller, Christian Laugier, Emilio Frazzoli, Mohan M. Trivedi, Dimitar P. Filev:
IEEE Transactions on Intelligent Vehicles Senior Associate Editors. IEEE Trans. Intell. Veh. 1(1): 3-5 (2016) - [j34]Bunyo Okumura, Michael R. James, Yusuke Kanzawa, Matthew Derry, Katsuhiro Sakai, Tomoki Nishi, Danil V. Prokhorov:
Challenges in Perception and Decision Making for Intelligent Automotive Vehicles: A Case Study. IEEE Trans. Intell. Veh. 1(1): 20-32 (2016) - [c52]Guangyu Zhong, Yi-Hsuan Tsai, Yi-Ting Chen, Xue Mei, Danil V. Prokhorov, Michael James, Ming-Hsuan Yang:
Learning to tell brake lights with convolutional features. ITSC 2016: 1558-1563 - [c51]Shuai Di, Honggang Zhang, Xue Mei, Danil V. Prokhorov, Haibin Ling:
A benchmark for cross-weather traffic scene understanding. ITSC 2016: 2150-2156 - [c50]Heng Fan, Xue Mei, Danil V. Prokhorov, Haibin Ling:
Cross datasets vegetation detection with spatial prior and local context. Intelligent Vehicles Symposium 2016: 735-740 - [i3]Heng Fan, Xue Mei, Danil V. Prokhorov, Haibin Ling:
Multi-level Contextual RNNs with Attention Model for Scene Labeling. CoRR abs/1607.02537 (2016) - 2015
- [j33]Zhen Ni, Haibo He, Dongbin Zhao, Xin Xu, Danil V. Prokhorov:
GrDHP: A General Utility Function Representation for Dual Heuristic Dynamic Programming. IEEE Trans. Neural Networks Learn. Syst. 26(3): 614-627 (2015) - [j32]Zhen Ni, Haibo He, Xiangnan Zhong, Danil V. Prokhorov:
Model-Free Dual Heuristic Dynamic Programming. IEEE Trans. Neural Networks Learn. Syst. 26(8): 1834-1839 (2015) - [j31]Xue Mei, Zhibin Hong, Danil V. Prokhorov, Dacheng Tao:
Robust Multitask Multiview Tracking in Videos. IEEE Trans. Neural Networks Learn. Syst. 26(11): 2874-2890 (2015) - [c48]Zhibin Hong, Zhe Chen, Chaohui Wang, Xue Mei, Danil V. Prokhorov, Dacheng Tao:
MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking. CVPR 2015: 749-758 - [c47]Shuai Di, Honggang Zhang, Xue Mei, Danil V. Prokhorov, Haibin Ling:
Spatial Prior for Nonparametric Road Scene Parsing. ITSC 2015: 1209-1214 - [c46]Xue Mei, Naoki Nagasaka, Bunyo Okumura, Danil V. Prokhorov:
Detection and motion planning for roadside parked vehicles at long distance. Intelligent Vehicles Symposium 2015: 412-418 - [i2]Alexander N. Gorban, Ivan Yu. Tyukin, Danil V. Prokhorov, Konstantin I. Sofeikov:
Approximation with Random Bases: Pro et Contra. CoRR abs/1506.04631 (2015) - 2014
- [j30]Michael Fairbank, Danil V. Prokhorov, Eduardo Alonso:
Clipping in Neurocontrol by Adaptive Dynamic Programming. IEEE Trans. Neural Networks Learn. Syst. 25(10): 1909-1920 (2014) - [c45]Pengpeng Liang, Yi Wu, Xue Mei, Jingyi Yu, Erik Blasch, Danil V. Prokhorov, Chunyuan Liao, Haitao Lang, Haibin Ling:
Blur-Resilient Tracking Using Group Sparsity. ACCV (5) 2014: 131-145 - [c44]Zhibin Hong, Chaohui Wang, Xue Mei, Danil V. Prokhorov, Dacheng Tao:
Tracking Using Multilevel Quantizations. ECCV (6) 2014: 155-171 - [c42]Konstantin I. Sofeikov, Ivan Tyukin, Alexander N. Gorban, Eugenij Moiseevich Mirkes, Danil V. Prokhorov, Ilya V. Romanenko:
Learning optimization for decision tree classification of non-categorical data with information gain impurity criterion. IJCNN 2014: 3548-3555 - 2013
- [j29]Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov:
An Equivalence Between Adaptive Dynamic Programming With a Critic and Backpropagation Through Time. IEEE Trans. Neural Networks Learn. Syst. 24(12): 2088-2100 (2013) - [c41]Zhibin Hong, Xue Mei, Danil V. Prokhorov, Dacheng Tao:
Tracking via Robust Multi-task Multi-view Joint Sparse Representation. ICCV 2013: 649-656 - [c40]Xiangnan Zhong, Haibo He, Danil V. Prokhorov:
Robust controller design of continuous-time nonlinear system using neural network. IJCNN 2013: 1-8 - 2012
- [j28]Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov:
Simple and Fast Calculation of the Second-Order Gradients for Globalized Dual Heuristic Dynamic Programming in Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 23(10): 1671-1676 (2012) - [c39]Zhen Ni, Haibo He, Dongbin Zhao, Danil V. Prokhorov:
Reinforcement learning control based on multi-goal representation using hierarchical heuristic dynamic programming. IJCNN 2012: 1-8 - [c38]Jing Wang, Haibo He, Danil V. Prokhorov:
A Folded Neural Network Autoencoder for Dimensionality Reduction. INNS-WC 2012: 120-127 - 2011
- [j27]Marco Baglietto, Lubica Benusková, Ivo Bukovsky, Tianping Chen, Tom Heskes, Kazushi Ikeda, Fakhri Karray, Rhee Man Kil, Robert Legenstein, Jinhu Lu, Yunqian Ma, Malik Magdon-Ismail, Michael G. Paulin, Robi Polikar, Danil V. Prokhorov, Marco A. Wiering, Vicente Zarzoso:
Editorial: One Year as EiC, and Editorial-Board Changes at TNN. IEEE Trans. Neural Networks 22(1): 1-7 (2011) - [c36]Zhen Ni, Haibo He, Danil V. Prokhorov, Jian Fu:
An online actor-critic learning approach with Levenberg-Marquardt algorithm. IJCNN 2011: 2333-2340 - 2009
- [c33]Ivan Tyukin, Danil V. Prokhorov:
Feasibility of random basis function approximators for modeling and control. CCA/ISIC 2009: 1391-1396 - [i1]Ivan Tyukin, Danil V. Prokhorov:
Feasibility of random basis function approximators for modeling and control. CoRR abs/0905.0677 (2009) - 2008
- [j23]Ivan Tyukin, Danil V. Prokhorov, Cees van Leeuwen:
Adaptive Classification of Temporal Signals in Fixed-Weight Recurrent Neural Networks: An Existence Proof. Neural Comput. 20(10): 2564-2596 (2008) - 2007
- [j21]Xiao Hu, Danil V. Prokhorov, Donald C. Wunsch II:
Time series prediction with a weighted bidirectional multi-stream extended Kalman filter. Neurocomputing 70(13-15): 2392-2399 (2007) - [j20]Ivan Tyukin, Danil V. Prokhorov, Cees van Leeuwen:
Adaptation and Parameter Estimation in Systems With Unstable Target Dynamics and Nonlinear Parametrization. IEEE Trans. Autom. Control. 52(9): 1543-1559 (2007) - [j18]Xindi Cai, Danil V. Prokhorov, Donald C. Wunsch II:
Training Winner-Take-All Simultaneous Recurrent Neural Networks. IEEE Trans. Neural Networks 18(3): 674-684 (2007) - [j17]Frank L. Lewis, Jie Huang, Thomas Parisini, Danil V. Prokhorov, Donald C. Wunsch II:
Guest Editorial Special Issue on Neural Networks for Feedback Control Systems. IEEE Trans. Neural Networks 18(4): 969-972 (2007) - 2005
- [j14]Danil V. Prokhorov, Daniel S. Levine, Fredric M. Ham, William Howell:
Welcome to the special issue. Neural Networks 18(5-6): 457- (2005) - [c16]Ivan Tyukin, Danil V. Prokhorov, Cees van Leeuwen:
A new method for adaptive brake control. ACC 2005: 2194-2199 - 2003
- [j12]Ivan Tyukin, Cees van Leeuwen, Danil V. Prokhorov:
Parameter Estimation of Sigmoid Superpositions: Dynamical System Approach. Neural Comput. 15(10): 2419-2455 (2003) - [j11]Lee A. Feldkamp, Danil V. Prokhorov, Timothy M. Feldkamp:
Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks. Neural Networks 16(5-6): 683-689 (2003) - [j10]Ivan Tyukin, Danil V. Prokhorov, Valery A. Terekhov:
Adaptive control with nonconvex parameterization. IEEE Trans. Autom. Control. 48(4): 554-567 (2003) - [c12]Ivan Tyukin, Danil V. Prokhorov, Cees van Leeuwen:
Finite form realizations of adaptive control algorithms. ECC 2003: 264-269 - 2002
- [c10]Ivan Tyukin, Cees van Leeuwen, Danil V. Prokhorov, Valery A. Terekhov:
On a problem of time-varying learning rate influence on the adaptive system dynamics. CDC 2002: 4718-4721 - 2000
- [j7]Arthur Petrosian, Danil V. Prokhorov, Richard Homan, Richard Dasheiff, Donald C. Wunsch II:
Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG. Neurocomputing 30(1-4): 201-218 (2000) - [j6]Paul H. Eaton, Danil V. Prokhorov, Donald C. Wunsch II:
Neurocontroller alternatives for "fuzzy" ball-and-beam systems with nonuniform nonlinear friction. IEEE Trans. Neural Networks Learn. Syst. 11(2): 423-435 (2000) - [c8]Valeri A. Terekhov, Ivan Yu. Tyukin, Danil V. Prokhorov:
Adaptive control on manifolds with RBF neural networks. CDC 2000: 3831-3836 - 1999
- [c7]Danil V. Prokhorov, Lee A. Feldkamp:
Application of SVM to Lyapunov function approximation. IJCNN 1999: 383-387 - 1998
- [j5]Emad W. Saad, Danil V. Prokhorov, Donald C. Wunsch II:
Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks. IEEE Trans. Neural Networks 9(6): 1456-1470 (1998) - [c6]Danil V. Prokhorov, Lee A. Feldkamp:
Analyzing for Lyapunov stability with adaptive critics. SMC 1998: 1658-1661 - 1997
- [j4]Danil V. Prokhorov, Donald C. Wunsch II:
Adaptive critic designs. IEEE Trans. Neural Networks 8(5): 997-1007 (1997) - [j3]Wang Song, Shaowei Xia, Jianchang Mao, Anil K. Jain, Danil V. Prokhorov, Donald C. Wunsch II:
Comments on "A self-organizing network for hyperellipsoidal clustering (HEC)" [and reply]. IEEE Trans. Neural Networks 8(6): 1561-1563 (1997) - [j2]Danil V. Prokhorov, Donald C. Wunsch:
Corrections To "Adaptive Critic Designs". IEEE Trans. Neural Networks 8(6): 1563 (1997) - [c5]Raonak Zaman, Danil V. Prokhorov, Donald C. Wunsch II:
Adaptive critic design in learning to play game of Go. ICNN 1997: 1-4 - [c4]Danil V. Prokhorov, Lee A. Feldkamp:
Primitive adaptive critics. ICNN 1997: 2263-2267 - [c3]Lee A. Feldkamp, Gintaras V. Puskorius, Danil V. Prokhorov:
Unified formulation for training recurrent networks with derivative adaptive critics. ICNN 1997: 2268-2272 - 1996
- [c2]Emad W. Saad, Danil V. Prokhorov, Donald C. Wunsch II:
Advanced neural network training methods for low false alarm stock trend prediction. ICNN 1996: 2021-2026 - 1995
- [j1]Danil V. Prokhorov, Roberto A. Santiago, Donald C. Wunsch II:
Adaptive critic designs: A case study for neurocontrol. Neural Networks 8(9): 1367-1372 (1995) - [c1]Hong Tan, Danil V. Prokhorov, Donald C. Wunsch:
Conservative thirty calendar day stock prediction using a probabilistic neural network. CIFEr 1995: 113-117
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