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Labels, Information, and Computation: Efficient, Privacy-Preserving Learning Using Sufficient Labels


Apr 19, 2021
Shiyu Duan, Jose C. Principe


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A Kernel Framework to Quantify a Model's Local Predictive Uncertainty under Data Distributional Shifts


Mar 02, 2021
Rishabh Singh, Jose C. Principe


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Annotating Motion Primitives for Simplifying Action Search in Reinforcement Learning


Feb 24, 2021
Isaac J. Sledge, Darshan W. Bryner, Jose C. Principe

* Submitted to IEEE Transactions on Emerging Topics in Computational Intelligence 

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Faster Convergence in Deep-Predictive-Coding Networks to Learn Deeper Representations


Feb 05, 2021
Isaac J. Sledge, Jose C. Principe

* Submitted to IEEE TNNLS 

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Deep Deterministic Information Bottleneck with Matrix-based Entropy Functional


Jan 31, 2021
Xi Yu, Shujian Yu, Jose C. Principe

* Accepted at ICASSP-21. Code available at https://github.com/yuxi120407/DIB. Extended version of the suppelementary material in "Measuring the Dependence with Matrix-based Entropy Functional", AAAI-21, arXiv:2101.10160 

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Measuring Dependence with Matrix-based Entropy Functional


Jan 25, 2021
Shujian Yu, Francesco Alesiani, Xi Yu, Robert Jenssen, Jose C. Principe

* Accepted at AAAI-21. An interpretable and differentiable dependence (or independence) measure that can be used to 1) train deep network under covariate shift and non-Gaussian noise; 2) implement a deep deterministic information bottleneck; and 3) understand the dynamics of learning of CNN. Code available at https://bit.ly/AAAI-dependence 

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Target Detection and Segmentation in Circular-Scan Synthetic-Aperture-Sonar Images using Semi-Supervised Convolutional Encoder-Decoders


Jan 10, 2021
Isaac J. Sledge, Matthew S. Emigh, Jonathan L. King, Denton L. Woods, J. Tory Cobb, Jose C. Principe

* Submitted to IEEE JOE 

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Training Deep Architectures Without End-to-End Backpropagation: A Brief Survey


Jan 09, 2021
Shiyu Duan, Jose C. Principe


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Unsupervised Foveal Vision Neural Networks with Top-Down Attention


Oct 18, 2020
Ryan Burt, Nina N. Thigpen, Andreas Keil, Jose C. Principe

* 29 pages, 15 figures 

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PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders


Jul 13, 2020
Yanjun Li, Shujian Yu, Jose C. Principe, Xiaolin Li, Dapeng Wu


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Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications


May 05, 2020
Shujian Yu, Ammar Shaker, Francesco Alesiani, Jose C. Principe

* accepted at IJCAI 20, code is available at https://github.com/SJYuCNEL/Bregman-Correntropy-Conditional-Divergence 

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Towards a Kernel based Physical Interpretation of Model Uncertainty


Feb 21, 2020
Rishabh Singh, Jose C. Principe


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Fast Estimation of Information Theoretic Learning Descriptors using Explicit Inner Product Spaces


Jan 01, 2020
Kan Li, Jose C. Principe

* 10 pages, 3 figures, 2 tables. arXiv admin note: text overlap with arXiv:1912.04530 

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No-Trick (Treat) Kernel Adaptive Filtering using Deterministic Features


Dec 10, 2019
Kan Li, Jose C. Principe

* 12 pages, 7 figures 

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Functional Bayesian Filter


Nov 24, 2019
Kan Li, Jose C. Principe

* 15 pages, 8 figures 

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Algorithmic Design and Implementation of Unobtrusive Multistatic Serial LiDAR Image


Nov 08, 2019
Chi Ding, Zheng Cao, Matthew S. Emigh, Jose C. Principe, Bing Ouyang, Anni Vuorenkoski, Fraser Dalgleish, Brian Ramos, Yanjun Li


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Multiscale Principle of Relevant Information for Hyperspectral Image Classification


Jul 13, 2019
Yantao Wei, Shujian Yu, Jose C. Principe


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Maximum Correntropy Criterion with Variable Center


Apr 13, 2019
Badong Chen, Xin Wang, Yingsong Li, Jose C. Principe

* 5 pages, 1 figure 

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An Exact Reformulation of Feature-Vector-based Radial-Basis-Function Networks for Graph-based Observations


Jan 22, 2019
Isaac J. Sledge, Jose C. Principe

* Submitted to the IEEE Transactions on Neural Networks and Learning Systems 

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Theory and Algorithms for Pulse Signal Processing


Dec 31, 2018
Gabriel Nallathambi, Jose C. Principe


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Simple stopping criteria for information theoretic feature selection


Nov 29, 2018
Shujian Yu, Jose C. Principe

* 4 pages, 2 figures 

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Understanding Convolutional Neural Network Training with Information Theory


Oct 12, 2018
Shujian Yu, Kristoffer Wickstrøm, Robert Jenssen, Jose C. Principe

* substantial improvement over v1 

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Understanding Autoencoders with Information Theoretic Concepts


Aug 23, 2018
Shujian Yu, Jose C. Principe

* 64 pages, 16 figures 

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Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional


Aug 23, 2018
Shujian Yu, Luis Gonzalo Sanchez Giraldo, Robert Jenssen, Jose C. Principe

* 26 pages, 8 figures 

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Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels


Jun 28, 2018
Shujian Yu, Xiaoyang Wang, Jose C. Principe

* Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (2018) 3033-3039 
* Published as a conference paper at IJCAI 2018 

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An Analysis of the Value of Information when Exploring Stochastic, Discrete Multi-Armed Bandits


Mar 03, 2018
Isaac J. Sledge, Jose C. Principe

* Entropy 

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Guided Policy Exploration for Markov Decision Processes using an Uncertainty-Based Value-of-Information Criterion


Feb 05, 2018
Isaac J. Sledge, Matthew S. Emigh, Jose C. Principe

* IEEE Transactions on Neural Networks and Learning Systems 

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Augmented Space Linear Model


Feb 02, 2018
Zhengda Qin, Badong Chen, Nanning Zheng, Jose C. Principe

* 5 pages and 1 figures 

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