


Остановите войну!
for scientists:


default search action
José C. Príncipe
José Carlos Príncipe
Person information

- affiliation: University of Florida, Gainesville, USA
Refine list

refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
- [j275]Yantao Wei, Shujian Yu
, Luis G. Sánchez Giraldo, José C. Príncipe:
Multiscale principle of relevant information for hyperspectral image classification. Mach. Learn. 112(4): 1227-1252 (2023) - [i70]Hongming Li, Shujian Yu, José C. Príncipe:
Causal Recurrent Variational Autoencoder for Medical Time Series Generation. CoRR abs/2301.06574 (2023) - [i69]Shujian Yu, Hongming Li, Sigurd Løkse, Robert Jenssen, José C. Príncipe:
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making. CoRR abs/2301.08970 (2023) - 2022
- [j274]Shiyu Duan
, José C. Príncipe:
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods. IEEE Comput. Intell. Mag. 17(4): 39-51 (2022) - [j273]Hongming Li, Ran Dou, Andreas Keil, José C. Príncipe
:
A self-learning cognitive architecture exploiting causality from rewards. Neural Networks 150: 274-292 (2022) - [j272]Isaac J. Sledge
, Darshan W. Bryner
, José C. Príncipe:
Annotating Motion Primitives for Simplifying Action Search in Reinforcement Learning. IEEE Trans. Emerg. Top. Comput. Intell. 6(5): 1137-1156 (2022) - [j271]Shiyu Duan
, Shujian Yu
, José C. Príncipe
:
Modularizing Deep Learning via Pairwise Learning With Kernels. IEEE Trans. Neural Networks Learn. Syst. 33(4): 1441-1451 (2022) - [j270]Kan Li
, José C. Príncipe
:
Functional Bayesian Filter. IEEE Trans. Signal Process. 70: 57-71 (2022) - [c362]Hongming Li, Shujian Yu, José C. Príncipe:
Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing. ICASSP 2022: 3878-3882 - [c361]Spencer Chang, José C. Príncipe:
Explaining Deep and ResNet Architecture Choices with Information Flow. IJCNN 2022: 1-6 - [c360]Ran Dou, José C. Príncipe:
The Extended Kernel Adaptive Autoregressive-Moving-Average Algorithm. IJCNN 2022: 1-6 - [c359]Pingping Zhu, José C. Príncipe:
Kernel Nonlinear Dynamic System Identification Based on Expectation-Maximization Method. IJCNN 2022: 1-10 - [c358]Roman V. Belavkin
, Panos M. Pardalos
, José C. Príncipe:
Value of Information in the Mean-Square Case and Its Application to the Analysis of Financial Time-Series Forecast. LION 2022: 549-563 - [c357]Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, José C. Príncipe:
Principle of relevant information for graph sparsification. UAI 2022: 2331-2341 - [i68]Hongming Li, Shujian Yu, José C. Príncipe:
Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing. CoRR abs/2202.02951 (2022) - [i67]Leila Kalantari, José C. Príncipe, Kathryn E. Sieving:
Hierarchical Linear Dynamical System for Representing Notes from Recorded Audio. CoRR abs/2202.13255 (2022) - [i66]Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, José C. Príncipe:
Principle of Relevant Information for Graph Sparsification. CoRR abs/2206.00118 (2022) - [i65]Rishabh Singh, José C. Príncipe:
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS. CoRR abs/2211.01999 (2022) - [i64]Rishabh Singh, José C. Príncipe:
Robust Dependence Measure using RKHS based Uncertainty Moments and Optimal Transport. CoRR abs/2211.02005 (2022) - [i63]Bo Hu, José C. Príncipe:
The Cross Density Kernel Function: A Novel Framework to Quantify Statistical Dependence for Random Processes. CoRR abs/2212.04631 (2022) - [i62]Isaac J. Sledge, José C. Príncipe:
Adapting the Exploration Rate for Value-of-Information-Based Reinforcement Learning. CoRR abs/2212.11083 (2022) - 2021
- [j269]Kan Li
, José C. Príncipe:
Biologically-Inspired Pulse Signal Processing for Intelligence at the Edge. Frontiers Artif. Intell. 4: 568384 (2021) - [j268]Jianji Wang, Pei Chen, Nanning Zheng, Badong Chen
, José C. Príncipe, Fei-Yue Wang:
Associations between MSE and SSIM as cost functions in linear decomposition with application to bit allocation for sparse coding. Neurocomputing 422: 139-149 (2021) - [j267]Feiya Lv, Shujian Yu, Chenglin Wen, José C. Príncipe:
Interpretable fault detection using projections of mutual information matrix. J. Frankl. Inst. 358(7): 4028-4057 (2021) - [j266]Rishabh Singh, José C. Príncipe:
Toward a Kernel-Based Uncertainty Decomposition Framework for Data and Models. Neural Comput. 33(5): 1164-1198 (2021) - [j265]Ryan Burt, Nina N. Thigpen, Andreas Keil, José C. Príncipe
:
Unsupervised foveal vision neural architecture with top-down attention. Neural Networks 141: 145-159 (2021) - [j264]Yiwen Wang
, José C. Príncipe
:
Reinforcement Learning in Reproducing Kernel Hilbert Spaces: Enabling Continuous Brain?Machine Interface Adaptation. IEEE Signal Process. Mag. 38(4): 34-45 (2021) - [j263]Shujian Yu
, Kristoffer Wickstrøm
, Robert Jenssen
, José C. Príncipe:
Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration. IEEE Trans. Neural Networks Learn. Syst. 32(1): 435-442 (2021) - [j262]Badong Chen
, Lei Xing
, Haiquan Zhao
, Shaoyi Du
, José C. Príncipe
:
Effects of Outliers on the Maximum Correntropy Estimation: A Robustness Analysis. IEEE Trans. Syst. Man Cybern. Syst. 51(6): 4007-4012 (2021) - [j261]Badong Chen
, Lujuan Dang
, Yuantao Gu
, Nanning Zheng
, José C. Príncipe
:
Minimum Error Entropy Kalman Filter. IEEE Trans. Syst. Man Cybern. Syst. 51(9): 5819-5829 (2021) - [j260]Bo Hu
, José C. Príncipe
:
MIMO Modeling by Learning Explicitly the Projection Space: The Maximum Correlation Ratio Cost Function. IEEE Trans. Signal Process. 69: 6039-6054 (2021) - [c356]Shujian Yu, Francesco Alesiani, Xi Yu, Robert Jenssen, José C. Príncipe:
Measuring Dependence with Matrix-based Entropy Functional. AAAI 2021: 10781-10789 - [c355]Bo Hu, José C. Príncipe:
Training a Bank of Wiener Models with a Novel Quadratic Mutual Information Cost Function. ICASSP 2021: 3150-3154 - [c354]Xi Yu
, Shujian Yu, José C. Príncipe:
Deep Deterministic Information Bottleneck with Matrix-Based Entropy Functional. ICASSP 2021: 3160-3164 - [c353]Shujian Yu, Luis G. Sánchez Giraldo, José C. Príncipe:
Information-Theoretic Methods in Deep Neural Networks: Recent Advances and Emerging Opportunities. IJCAI 2021: 4669-4678 - [c352]Hongming Li, José C. Príncipe:
Speeding Up Reinforcement Learning by Exploiting Causality in Reward Sequences. IJCNN 2021: 1-6 - [c351]Shailaja Akella, Ali Mohebi, Kierstin Riels, Andreas Keil, Karim G. Oweiss, José C. Príncipe:
Local power estimation of neuromodulations using point process modeling. NER 2021: 420-425 - [i61]Shiyu Duan, José C. Príncipe:
Training Deep Architectures Without End-to-End Backpropagation: A Brief Survey. CoRR abs/2101.03419 (2021) - [i60]Isaac J. Sledge, Matthew S. Emigh, Jonathan L. King, Denton L. Woods, J. Tory Cobb, José C. Príncipe:
Target Detection and Segmentation in Circular-Scan Synthetic-Aperture-Sonar Images using Semi-Supervised Convolutional Encoder-Decoders. CoRR abs/2101.03603 (2021) - [i59]Isaac J. Sledge, José C. Príncipe:
Faster Convergence in Deep-Predictive-Coding Networks to Learn Deeper Representations. CoRR abs/2101.06848 (2021) - [i58]Shujian Yu, Francesco Alesiani, Xi Yu, Robert Jenssen, José C. Príncipe:
Measuring Dependence with Matrix-based Entropy Functional. CoRR abs/2101.10160 (2021) - [i57]Xi Yu, Shujian Yu, José C. Príncipe:
Deep Deterministic Information Bottleneck with Matrix-based Entropy Functional. CoRR abs/2102.00533 (2021) - [i56]Isaac J. Sledge, Darshan W. Bryner, José C. Príncipe:
Annotating Motion Primitives for Simplifying Action Search in Reinforcement Learning. CoRR abs/2102.12017 (2021) - [i55]Rishabh Singh, José C. Príncipe:
A Kernel Framework to Quantify a Model's Local Predictive Uncertainty under Data Distributional Shifts. CoRR abs/2103.01374 (2021) - [i54]Shiyu Duan, José C. Príncipe:
Labels, Information, and Computation: Efficient, Privacy-Preserving Learning Using Sufficient Labels. CoRR abs/2104.09015 (2021) - [i53]Isaac J. Sledge, José C. Príncipe:
An Information-Theoretic Approach for Automatically Determining the Number of States when Aggregating Markov Chains. CoRR abs/2107.01799 (2021) - [i52]Isaac J. Sledge, Christopher D. Toole, Joseph A. Maestri, José C. Príncipe:
External-Memory Networks for Low-Shot Learning of Targets in Forward-Looking-Sonar Imagery. CoRR abs/2107.10504 (2021) - [i51]Leila Kalantari, José C. Príncipe, Kathryn E. Sieving:
Uncertainty quantification for multiclass data description. CoRR abs/2108.12857 (2021) - [i50]Rishabh Singh, José C. Príncipe:
Quantifying Model Predictive Uncertainty with Perturbation Theory. CoRR abs/2109.10888 (2021) - [i49]Isaac J. Sledge, José C. Príncipe:
Estimating Rényi's α-Cross-Entropies in a Matrix-Based Way. CoRR abs/2109.11737 (2021) - [i48]Bo Hu, Shujian Yu, José C. Príncipe:
Information Theoretic Structured Generative Modeling. CoRR abs/2110.05794 (2021) - 2020
- [j259]José C. Príncipe:
IEEE Fellows?Class of 2020 [Society Briefs]. IEEE Comput. Intell. Mag. 15(2): 6-10 (2020) - [j258]Jianyi Liu
, José C. Príncipe, Arash Andalib
:
Fast spatio-temporal decorrelation using FIR filter network with decoupled adaptive step sizes. Digit. Signal Process. 96 (2020) - [j257]Shiyu Duan, Shujian Yu, Yunmei Chen
, José C. Príncipe:
On Kernel Method-Based Connectionist Models and Supervised Deep Learning Without Backpropagation. Neural Comput. 32(1): 97-135 (2020) - [j256]Shujian Yu
, Luis Gonzalo Sánchez Giraldo
, Robert Jenssen
, José C. Príncipe
:
Multivariate Extension of Matrix-Based Rényi's $\alpha$α-Order Entropy Functional. IEEE Trans. Pattern Anal. Mach. Intell. 42(11): 2960-2966 (2020) - [j255]Ying Ma
, Joseph Brooks, Hongming Li, José C. Príncipe
:
Procedural Memory Augmented Deep Reinforcement Learning. IEEE Trans. Artif. Intell. 1(2): 105-120 (2020) - [j254]Gabriel Nallathambi
, José C. Príncipe
:
Theory and Algorithms for Pulse Signal Processing. IEEE Trans. Circuits Syst. I Regul. Pap. 67-I(8): 2707-2718 (2020) - [j253]Ying Ma
, José C. Príncipe
:
A Taxonomy for Neural Memory Networks. IEEE Trans. Neural Networks Learn. Syst. 31(6): 1780-1793 (2020) - [j252]Zhengda Qin
, Badong Chen
, Yuantao Gu
, Nanning Zheng, José C. Príncipe
:
Probability Density Rank-Based Quantization for Convex Universal Learning Machines. IEEE Trans. Neural Networks Learn. Syst. 31(8): 3100-3113 (2020) - [j251]Isaac J. Sledge
, José C. Príncipe:
An Exact Reformulation of Feature-Vector-Based Radial-Basis-Function Networks for Graph-Based Observations. IEEE Trans. Neural Networks Learn. Syst. 31(11): 4990-4998 (2020) - [j250]Zhengda Qin
, Badong Chen
, Nanning Zheng, José C. Príncipe
:
Augmented Space Linear Models. IEEE Trans. Signal Process. 68: 2724-2738 (2020) - [c350]Rishabh Singh, Shujian Yu, José C. Príncipe:
Composite Dynamic Texture Synthesis Using Hierarchical Linear Dynamical System. ICASSP 2020: 2757-2761 - [c349]José C. Príncipe:
A Cognitive Architecture for Object Recognition in Video. ICMLA 2020: 39 - [c348]Shujian Yu
, Ammar Shaker, Francesco Alesiani
, José C. Príncipe:
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications. IJCAI 2020: 2777-2784 - [c347]Hongming Li, Ying Ma, José C. Príncipe:
Cognitive Architecture for Video Games. IJCNN 2020: 1-9 - [c346]Isaac J. Sledge, José C. Príncipe:
Regularized Training of Convolutional Autoencoders using the Rényi-Stratonovich Value of Information. IJCNN 2020: 1-7 - [c345]Rishabh Singh, José C. Príncipe:
Time Series Analysis using a Kernel based Multi-Modal Uncertainty Decomposition Framework. UAI 2020: 1368-1377 - [i47]Kan Li, José C. Príncipe:
Fast Estimation of Information Theoretic Learning Descriptors using Explicit Inner Product Spaces. CoRR abs/2001.00265 (2020) - [i46]Rishabh Singh
, José C. Príncipe:
Towards a Kernel based Physical Interpretation of Model Uncertainty. CoRR abs/2001.11495 (2020) - [i45]Shujian Yu, Ammar Shaker, Francesco Alesiani, José C. Príncipe:
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications. CoRR abs/2005.02196 (2020) - [i44]Shiyu Duan, Shujian Yu, José C. Príncipe:
Modularizing Deep Learning via Pairwise Learning With Kernels. CoRR abs/2005.05541 (2020) - [i43]Yanjun Li, Shujian Yu, José C. Príncipe, Xiaolin Li, Dapeng Oliver Wu:
PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders. CoRR abs/2007.06503 (2020) - [i42]Feiya Lv, Shujian Yu, Chenglin Wen, José C. Príncipe:
Mutual Information Matrix for Interpretable Fault Detection. CoRR abs/2007.10692 (2020) - [i41]Ryan Burt, Nina N. Thigpen, Andreas Keil, José C. Príncipe:
Unsupervised Foveal Vision Neural Networks with Top-Down Attention. CoRR abs/2010.09103 (2020)
2010 – 2019
- 2019
- [j249]José C. Príncipe:
IEEE Fellows - Class of 2019 [Society Briefs]. IEEE Comput. Intell. Mag. 14(2): 9-12 (2019) - [j248]Shujian Yu
, José C. Príncipe:
Simple Stopping Criteria for Information Theoretic Feature Selection. Entropy 21(1): 99 (2019) - [j247]Isaac J. Sledge
, José C. Príncipe:
Reduction of Markov Chains Using a Value-of-Information-Based Approach. Entropy 21(4): 349 (2019) - [j246]Shujian Yu
, Zubin Abraham, Heng Wang, Mohak Shah, Yantao Wei, José C. Príncipe:
Concept drift detection and adaptation with hierarchical hypothesis testing. J. Frankl. Inst. 356(5): 3187-3215 (2019) - [j245]Eleni I. Georga, José C. Príncipe, Dimitrios I. Fotiadis
:
Short-term prediction of glucose in type 1 diabetes using kernel adaptive filters. Medical Biol. Eng. Comput. 57(1): 27-46 (2019) - [j244]Shujian Yu
, José C. Príncipe:
Understanding autoencoders with information theoretic concepts. Neural Networks 117: 104-123 (2019) - [j243]Badong Chen
, Xin Wang, Yingsong Li
, José C. Príncipe:
Maximum Correntropy Criterion With Variable Center. IEEE Signal Process. Lett. 26(8): 1212-1216 (2019) - [j242]Lujuan Dang, Badong Chen
, Shiyuan Wang
, Yuantao Gu
, José C. Príncipe
:
Kernel Kalman Filtering With Conditional Embedding and Maximum Correntropy Criterion. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(11): 4265-4277 (2019) - [j241]Isaac John Sledge, José C. Príncipe:
Analysis of Agent Expertise in Ms. Pac-Man Using Value-of-Information-Based Policies. IEEE Trans. Games 11(2): 142-158 (2019) - [j240]Badong Chen
, Lei Xing
, Nanning Zheng, José C. Príncipe:
Quantized Minimum Error Entropy Criterion. IEEE Trans. Neural Networks Learn. Syst. 30(5): 1370-1380 (2019) - [c344]Shailaja Akella, José C. Príncipe:
Correntropy based Robust Decomposition of Neuromodulations. EMBC 2019: 5790-5793 - [c343]Isaac J. Sledge, José C. Príncipe:
A Differential-geometric Approach for Globally Solving a Non-convex, Discontinuous Depth Estimation Problem for Plenoptic Camera Images. ICASSP 2019: 2267-2271 - [c342]Isaac J. Sledge, José C. Príncipe:
An Information-theoretic Approach for Automatically Determining the Number of State Groups When Aggregating Markov Chains. ICASSP 2019: 3612-3616 - [c341]Mihael Cudic, José C. Príncipe:
Using a Recurrent Kernel Learning Machine for Small-Sample Image Classification. IJCNN 2019: 1-6 - [c340]Xi Yu
, Ying Ma, Stephanie Farrington, John Reed, Bing Ouyang, José C. Príncipe:
Fast segmentation for large and sparsely labeled coral images. IJCNN 2019: 1-6 - [c339]Carlos A. Loza, José C. Príncipe:
The Generalized Sleep Spindles Detector: A Generative Model Approach on Single-Channel EEGs. IWANN (1) 2019: 127-138 - [c338]Carlos A. Loza, José C. Príncipe:
Sparse Wave Packets Discriminate Motor Tasks in EEG-based BCIs. NER 2019: 639-642 - [i40]Gabriel Nallathambi, José C. Príncipe:
Theory and Algorithms for Pulse Signal Processing. CoRR abs/1901.01140 (2019) - [i39]Isaac J. Sledge, José C. Príncipe:
An Exact Reformulation of Feature-Vector-based Radial-Basis-Function Networks for Graph-based Observations. CoRR abs/1901.07484 (2019) - [i38]Isaac J. Sledge, José C. Príncipe:
Reduction of Markov Chains using a Value-of-Information-Based Approach. CoRR abs/1903.09266 (2019) - [i37]Badong Chen, Xin Wang, Yingsong Li, José C. Príncipe:
Maximum Correntropy Criterion with Variable Center. CoRR abs/1904.06501 (2019) - [i36]Badong Chen, Lujuan Dang, Yuantao Gu, Nanning Zheng, José C. Príncipe:
Minimum Error Entropy Kalman Filter. CoRR abs/1904.06617 (2019) - [i35]Yantao Wei, Shujian Yu, José C. Príncipe:
Multiscale Principle of Relevant Information for Hyperspectral Image Classification. CoRR abs/1907.06022 (2019) - [i34]Kristoffer Wickstrøm, Sigurd Løkse, Michael Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen:
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels. CoRR abs/1909.11396 (2019) - [i33]Chi Ding, Zheng Cao, Matthew S. Emigh, José C. Príncipe, Bing Ouyang, Anni K. Vuorenkoski, Fraser R. Dalgleish, Brian Ramos, Yanjun Li:
Algorithmic Design and Implementation of Unobtrusive Multistatic Serial LiDAR Image. CoRR abs/1911.03267 (2019) - [i32]Kan Li, José C. Príncipe:
Functional Bayesian Filter. CoRR abs/1911.10606 (2019) - [i31]Kan Li, José C. Príncipe:
No-Trick (Treat) Kernel Adaptive Filtering using Deterministic Features. CoRR abs/1912.04530 (2019) - 2018
- [j239]José C. Príncipe:
2018 IEEE CIS Awards [Society Briefs]. IEEE Comput. Intell. Mag. 13(1): 10-12 (2018) - [j238]Isaac J. Sledge
, José C. Príncipe:
An Analysis of the Value of Information When Exploring Stochastic, Discrete Multi-Armed Bandits. Entropy 20(3): 155 (2018) - [j237]João P. F. Guimarães, Aluisio I. Rêgo Fontes, Joilson B. A. Rego, Allan de M. Martins
, José C. Príncipe:
Complex correntropy function: Properties, and application to a channel equalization problem. Expert Syst. Appl. 107: 173-181 (2018) - [j236]Mihael Cudic
, Ryan Burt, Eder Santana, José C. Príncipe:
A flexible testing environment for visual question answering with performance evaluation. Neurocomputing 291: 128-135 (2018) - [j235]Xiaowei Gu, Plamen Angelov, Dmitry Kangin, José C. Príncipe:
Self-Organised direction aware data partitioning algorithm. Inf. Sci. 423: 80-95 (2018) - [j234]Xiaowei Gu
, Plamen P. Angelov
, José C. Príncipe:
A method for autonomous data partitioning. Inf. Sci. 460-461: 65-82 (2018) - [j233]Goktug T. Cinar
, Pedro M. N. Sequeira
, José C. Príncipe:
Hierarchical linear dynamical systems for unsupervised musical note recognition. J. Frankl. Inst. 355(4): 1638-1662 (2018) - [j232]Stefan Craciun, Robert Kirchgessner, Alan D. George, Herman Lam, José C. Príncipe:
A real-time, power-efficient architecture for mean-shift image segmentation. J. Real Time Image Process. 14(2): 379-394 (2018) - [j231]Plamen P. Angelov
, Xiaowei Gu
, José C. Príncipe:
A Generalized Methodology for Data Analysis. IEEE Trans. Cybern. 48(10): 2981-2993 (2018) - [j230]Zhirong Luan, Hua Qu, Ji-hong Zhao, Badong Chen
, José C. Príncipe:
Fairness constrained diffusion adaptive power control for dense small cell network. Telecommun. Syst. 68(2): 373-384 (2018) - [j229]Plamen P. Angelov
, Xiaowei Gu
, José C. Príncipe:
Autonomous Learning Multimodel Systems From Data Streams. IEEE Trans. Fuzzy Syst. 26(4): 2213-2224 (2018) - [j228]Guibiao Xu
, Bao-Gang Hu
, José C. Príncipe:
Robust C-Loss Kernel Classifiers. IEEE Trans. Neural Networks Learn. Syst. 29(3): 510-522 (2018) - [j227]Badong Chen
, Lei Xing, Bin Xu, Haiquan Zhao, José C. Príncipe:
Insights Into the Robustness of Minimum Error Entropy Estimation. IEEE Trans. Neural Networks Learn. Syst. 29(3): 731-737 (2018) - [j226]Dongbin Zhao
, Derong Liu
, Frank L. Lewis, José C. Príncipe, Stefano Squartini
:
Special Issue on Deep Reinforcement Learning and Adaptive Dynamic Programming. IEEE Trans. Neural Networks Learn. Syst. 29(6): 2038-2041 (2018) - [j225]Isaac J. Sledge
, Matthew S. Emigh, José C. Príncipe:
Guided Policy Exploration for Markov Decision Processes Using an Uncertainty-Based Value-of-Information Criterion. IEEE Trans. Neural Networks Learn. Syst. 29(6): 2080-2098 (2018) - [j224]Eder Santana
, Matthew S. Emigh
, Pablo Zegers, José C. Príncipe:
Exploiting Spatio-Temporal Structure With Recurrent Winner-Take-All Networks. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3738-3746 (2018) - [c337]Shailaja Akella, José C. Príncipe:
Quantitative Analysis of a Marked Point Process based Sleep Spindle Detector (MPP-SSD). EMBC 2018: 1464-1467 - [c336]Carlos A. Loza, José C. Príncipe:
The Embedding Transform. A Novel Analysis of Non-Stationarity in the EEG. EMBC 2018: 3112-3115 - [c335]Xiang Zhang, José C. Príncipe, Yiwen Wang:
Clustering Based Kernel Reinforcement Learning for Neural Adaptation in Brain-Machine Interfaces. EMBC 2018: 6125-6128 - [c334]Ying Ma, Bing Ouyang, Stephanie Farrington, Shujian Yu, John Reed, José C. Príncipe:
Joint Image Segmentation and Classification with Application to Cluttered Coral Images. GlobalSIP 2018: 365-369 - [c333]Isaac J. Sledge, José C. Príncipe:
Partitioning Relational Matrices of Similarities or Dissimilarities Using the Value of Information. ICASSP 2018: 2416-2420 - [c332]Rishabh Singh