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researcher

J. Príncipe

82 papers hereh-index 8633.7k citations1.2k works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author9
  • last author72

Across the 81 of 82 papers where every author was matched, so the position is known.

fields
  • cs.LG35
  • eess.SP9
  • stat.ML8
  • cs.CV6
  • cs.IT6
  • astro-ph.IM4
same name
  • J. Príncipe — 4 papers, h 1
  • J. Príncipe — 1 paper, h 14

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092024
most citedGeneralized Correntropy for Robust Adaptive Filtering

780 citations · 1.8k across the 76 of their papers we have counts for

collaborators
Showing 2016Show all

4 papers · 1 filter

cs.ET2016★ 2 cited

Signal Processing with Pulse Trains: An Algebraic Approach- Part II

Gabriel Nallathambi, Jose Principe

The integrate and fire converter (IFC) enables an alternative to digital signal processing. IFC converts analog signal voltages into time between pulses and it is possible to recon…

cs.LG2016★ 2 cited

Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks

Eder Santana, Matthew Emigh, Pablo Zegers +1

We propose a convolutional recurrent neural network, with Winner-Take-All dropout for high dimensional unsupervised feature learning in multi-dimensional time series. We apply the…

stat.ML2016★ 191 cited

Kernel Risk-Sensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering

Badong Chen, Lei Xing, Bin Xu +3

Nonlinear similarity measures defined in kernel space, such as correntropy, can extract higher-order statistics of data and offer potentially significant performance improvement ov…

cs.LG2016

Information Theoretic-Learning Auto-Encoder

Eder Santana, Matthew Emigh, Jose C Principe

We propose Information Theoretic-Learning (ITL) divergence measures for variational regularization of neural networks. We also explore ITL-regularized autoencoders as an alternativ…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.