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ORCIDJosé C. Príncipe
José Carlos Príncipe
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- affiliation: University of Florida, Gainesville, USA
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2020 – today
- 2024
[j281]Miguel Lima Teixeira
, João Pedro Oliveira, José C. Príncipe, João Goes:
A Standard-Cell-Based Neuro-Inspired Integrate-and-Fire Analog-to-Time Converter for Biological and Low-Frequency Signals - Comparison With Analog Version. IEEE Trans. Biomed. Circuits Syst. 18(4): 861-871 (2024)- [j280]Jing Yang, Yuehai Chen, Shaoyi Du, Badong Chen, José C. Príncipe:
IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction. IEEE Trans. Cybern. 54(7): 3904-3917 (2024) - [c371]Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, José C. Príncipe:
Cauchy-Schwarz Divergence Information Bottleneck for Regression. ICLR 2024 - [c370]Naoki Sawahashi, José C. Príncipe:
End-to-end Image Classification in Linear Hybrid Cellular Automata. IJCNN 2024: 1-6 - [c369]Rishabh Singh, Yaxin Ma, José C. Príncipe:
Finding Local Dependent Regions in PDFs using RKHS Uncertainty Moments and Optimal Transport. IJCNN 2024: 1-6 - [i76]Isaac J. Sledge, Dominic M. Byrne, Jonathan L. King, Steven H. Ostertag, Denton L. Woods, James L. Prater, Jermaine L. Kennedy, Timothy M. Marston, José C. Príncipe:
Weakly-Supervised Semantic Segmentation of Circular-Scan, Synthetic-Aperture-Sonar Imagery. CoRR abs/2401.11313 (2024) - [i75]Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, José C. Príncipe:
Cauchy-Schwarz Divergence Information Bottleneck for Regression. CoRR abs/2404.17951 (2024) - 2023
- [j279]Kristoffer K. Wickstrøm, Sigurd Løkse, Michael C. Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen:
Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. Entropy 25(6): 899 (2023) - [j278]Nan Liu, Badong Chen, José C. Príncipe:
Special issue on smart healthcare: artificial intelligence in biomedicine. J. Ambient Intell. Humaniz. Comput. 14(11): 15427 (2023) - [j277]Shiyu Duan, Spencer Chang, José C. Príncipe:
Labels, Information, and Computation: Efficient Learning Using Sufficient Labels. J. Mach. Learn. Res. 24: 31:1-31:35 (2023) - [j276]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) - [j275]Isaac J. Sledge, José C. Príncipe:
Faster Convergence in Deep-Predictive-Coding Networks to Learn Deeper Representations. IEEE Trans. Neural Networks Learn. Syst. 34(8): 5156-5170 (2023) - [c368]Hongming Li, Shujian Yu, José C. Príncipe:
Causal Recurrent Variational Autoencoder for Medical Time Series Generation. AAAI 2023: 8562-8570 - [c367]Miguel Lima Teixeira, João Pedro Oliveira, José C. Príncipe, João Goes:
A Standard-Cell-Based Neuro-Inspired Integrate-and-Fire ATC for Biological and Low-Frequency Signals. BioCAS 2023: 1-5 - [c366]Ran Dou, José C. Príncipe:
Universal Recurrent Event Memories for Streaming Data. IJCNN 2023: 1-10 - [c365]Ran Dou, José C. Príncipe:
Dynamic Analysis and an Eigen Initializer for Recurrent Neural Networks. IJCNN 2023: 1-6 - [c364]Yao Sun, Bo Hu, José C. Príncipe:
The Kernel Maximal Correlation Filter. MLSP 2023: 1-6 - [c363]Bo Hu, José C. Príncipe:
Cross Density Kernel for Nonstationary Signal Processing. SSP 2023: 195-199 - [i74]Hongming Li, Shujian Yu, José C. Príncipe:
Causal Recurrent Variational Autoencoder for Medical Time Series Generation. CoRR abs/2301.06574 (2023) - [i73]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) - [i72]Bo Hu, Yuheng Bu, José C. Príncipe:
Feature Learning in Image Hierarchies using Functional Maximal Correlation. CoRR abs/2305.20074 (2023) - [i71]Ran Dou, José C. Príncipe:
Dynamic Analysis and an Eigen Initializer for Recurrent Neural Networks. CoRR abs/2307.15679 (2023) - [i70]Ran Dou, José C. Príncipe:
Universal Recurrent Event Memories for Streaming Data. CoRR abs/2307.15694 (2023) - [i69]Benjamin Colburn, José C. Príncipe, Luis Gonzalo Sánchez Giraldo:
An Alternate View on Optimal Filtering in an RKHS. CoRR abs/2312.12318 (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]