Fernando Perez-Cruz

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ETH Zurich ∙ Universidad Carlos III de Madrid ∙ Stevens Institute of Technology

Robust Sampling in Deep Learning

Deep learning requires regularization mechanisms to reduce overfitting a...
06/04/2020 ∙ by Aurora Cobo Aguilera, et al. ∙ 0 ∙ share

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Improved BiGAN training with marginal likelihood equalization

We propose a novel training procedure for improving the performance of g...
11/04/2019 ∙ by Pablo Sánchez-Martín, et al. ∙ 8 ∙ share

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Probabilistic Time of Arrival Localization

In this paper, we take a new approach for time of arrival geo-localizati...
10/15/2019 ∙ by Fernando Perez-Cruz, et al. ∙ 0 ∙ share

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Probabilistic MIMO Symbol Detection with Expectation Consistency Approximate Inference

In this paper we explore low-complexity probabilistic algorithms for sof...
10/02/2019 ∙ by Javier Cépedes, et al. ∙ 0 ∙ share

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Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies

The recent adoption of Electronic Health Records (EHRs) by health care p...
04/29/2019 ∙ by Stefan G. Stark, et al. ∙ 0 ∙ share

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Out-of-Sample Testing for GANs

We propose a new method to evaluate GANs, namely EvalGAN. EvalGAN relies...
01/28/2019 ∙ by Pablo Sánchez-Martín, et al. ∙ 0 ∙ share

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Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation

New communication standards need to deal with machine-to-machine communi...
10/18/2018 ∙ by Francisco J. R. Ruiz, et al. ∙ 0 ∙ share

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Sparse Three-parameter Restricted Indian Buffet Process for Understanding International Trade

This paper presents a Bayesian nonparametric latent feature model specia...
06/29/2018 ∙ by Melanie F. Pradier, et al. ∙ 0 ∙ share

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PassGAN: A Deep Learning Approach for Password Guessing

State-of-the-art password guessing tools, such as HashCat and John the R...
09/01/2017 ∙ by Briland Hitaj, et al. ∙ 0 ∙ share

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Accelerated Inference for Latent Variable Models

Inference of latent feature models in the Bayesian nonparametric setting...
05/19/2017 ∙ by Michael Minyi Zhang, et al. ∙ 0 ∙ share

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Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Deep Learning has recently become hugely popular in machine learning, pr...
02/24/2017 ∙ by Briland Hitaj, et al. ∙ 0 ∙ share

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Complex-Valued Kernel Methods for Regression

Usually, complex-valued RKHS are presented as an straightforward applica...
10/31/2016 ∙ by Rafael Boloix-Tortosa, et al. ∙ 0 ∙ share

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Deep Learning for Multi-label Classification

In multi-label classification, the main focus has been to develop ways o...
12/17/2014 ∙ by Jesse Read, et al. ∙ 0 ∙ share

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Bayesian Nonparametric Crowdsourcing

Crowdsourcing has been proven to be an effective and efficient tool to a...
07/18/2014 ∙ by Pablo G. Moreno, et al. ∙ 0 ∙ share

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Bayesian nonparametric comorbidity analysis of psychiatric disorders

The analysis of comorbidity is an open and complex research field in the...
01/29/2014 ∙ by Francisco J. R. Ruiz, et al. ∙ 0 ∙ share

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Gaussian Processes for Nonlinear Signal Processing

Gaussian processes (GPs) are versatile tools that have been successfully...
03/12/2013 ∙ by Fernando Perez-Cruz, et al. ∙ 0 ∙ share

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Fernando Perez-Cruz

Featured Co-authors

Yee Whye Teh

Gunnar Rätsch

Lennart Svensson

Isabel Valera

Francisco J. R. Ruiz

Miguel Lázaro-Gredilla

Pablo M. Olmos

Jesse Read

Antonio Artés-Rodríguez

Steven Van Vaerenbergh

Stephanie L. Hyland

Robust Sampling in Deep Learning

Improved BiGAN training with marginal likelihood equalization

Probabilistic Time of Arrival Localization

Probabilistic MIMO Symbol Detection with Expectation Consistency Approximate Inference

Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies

Out-of-Sample Testing for GANs

Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation

Sparse Three-parameter Restricted Indian Buffet Process for Understanding International Trade

PassGAN: A Deep Learning Approach for Password Guessing

Accelerated Inference for Latent Variable Models

Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Complex-Valued Kernel Methods for Regression

Deep Learning for Multi-label Classification

Bayesian Nonparametric Crowdsourcing

Bayesian nonparametric comorbidity analysis of psychiatric disorders

Gaussian Processes for Nonlinear Signal Processing