@inproceedings{pmlr-v258-vary25ab,

title = {Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization},

author = {Simon Vary and David Mart\'{i}nez-Rubio and Patrick Rebeschini},

editor = {Yingzhen Li and Stephan Mandt and Shipra Agrawal and Emtiyaz Khan},

url = {https://proceedings.mlr.press/v258/vary25a.html},

year  = {2025},

date = {2025-05-01},

booktitle = {Proceedings of The 28th International Conference on Artificial Intelligence and Statistics},

volume = {258},

pages = {4942\textendash4950},

publisher = {PMLR},

series = {Proceedings of Machine Learning Research},

abstract = {We study first-order algorithms that are uniformly stable for empirical risk minimization (ERM) problems that are convex and smooth with respect to $p$-norms, $p geq 1$. We propose a black-box reduction method that, by employing properties of uniformly convex regularizers, turns an optimization algorithm for H\"{o}lder smooth convex losses into a uniformly stable learning algorithm with optimal statistical risk bounds on the excess risk, up to a constant factor depending on $p$. Achieving a black-box reduction for uniform stability was posed as an open question by Attia and Koren (2022), which had solved the Euclidean case $p=2$. We explore applications that leverage non-Euclidean geometry in addressing binary classification problems.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{pmlr-v258-vary25a,

title = {Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization},

author = {Simon Vary and David Mart\'{i}nez-Rubio and Patrick Rebeschini},

editor = {Yingzhen Li and Stephan Mandt and Shipra Agrawal and Emtiyaz Khan},

url = {https://proceedings.mlr.press/v258/vary25a.html},

year  = {2025},

date = {2025-05-01},

booktitle = {Proceedings of The 28th International Conference on Artificial Intelligence and Statistics},

volume = {258},

pages = {4942\textendash4950},

publisher = {PMLR},

series = {Proceedings of Machine Learning Research},

abstract = {We study first-order algorithms that are uniformly stable for empirical risk minimization (ERM) problems that are convex and smooth with respect to $p$-norms, $p geq 1$. We propose a black-box reduction method that, by employing properties of uniformly convex regularizers, turns an optimization algorithm for H\"{o}lder smooth convex losses into a uniformly stable learning algorithm with optimal statistical risk bounds on the excess risk, up to a constant factor depending on $p$. Achieving a black-box reduction for uniform stability was posed as an open question by Attia and Koren (2022), which had solved the Euclidean case $p=2$. We explore applications that leverage non-Euclidean geometry in addressing binary classification problems.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{pmlr-v258-martinez-rubio25a,

title = {Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties},

author = {David Mart\'{i}nez-Rubio and Christophe Roux and Christopher Criscitiello and Sebastian Pokutta},

editor = {Yingzhen Li and Stephan Mandt and Shipra Agrawal and Emtiyaz Khan},

url = {https://proceedings.mlr.press/v258/martinez-rubio25a.html},

year  = {2025},

date = {2025-05-01},

urldate = {2025-05-01},

booktitle = {Proceedings of The 28th International Conference on Artificial Intelligence and Statistics},

volume = {258},

pages = {280\textendash288},

publisher = {PMLR},

series = {Proceedings of Machine Learning Research},

abstract = {In this work, we study optimization problems of the form $min_x max_y f(x, y)$, where $f(x, y)$ is defined on a product Riemannian manifold $mathcalM times mathcalN$ and is $mu_x$-strongly geodesically convex (g-convex) in $x$ and $mu_y$-strongly g-concave in $y$, for $mu_x, mu_y geq 0$. We design accelerated methods when $f$ is $(L_x, L_y, L_xy)$-smooth and $mathcalM$, $mathcalN$ are Hadamard. To that aim we introduce new g-convex optimization results, of independent interest: we show global linear convergence for metric-projected Riemannian gradient descent and improve existing accelerated methods by reducing geometric constants. Additionally, we complete the analysis of two previous works applying to the Riemannian min-max case by removing an assumption about iterates staying in a pre-specified compact set.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{pmlr-v238-frutos24a,

title = {Training Implicit Generative Models via an Invariant Statistical Loss},

author = {Jos\'{e} Manuel Frutos and Pablo Olmos and Manuel Alberto Vazquez Lopez and Joaqu\'{i}n M\'{i}guez},

editor = {Sanjoy Dasgupta and Stephan Mandt and Yingzhen Li},

url = {https://proceedings.mlr.press/v238/frutos24a.html},

year  = {2024},

date = {2024-05-01},

booktitle = {Proceedings of The 27th International Conference on Artificial Intelligence and Statistics},

volume = {238},

pages = {2026\textendash2034},

publisher = {PMLR},

series = {Proceedings of Machine Learning Research},

abstract = {Implicit generative models have the capability to learn arbitrary complex data distributions. On the downside, training requires telling apart real data from artificially-generated ones using adversarial discriminators, leading to unstable training and mode-dropping issues. As reported by Zahee et al. (2017), even in the one-dimensional (1D) case, training a generative adversarial network (GAN) is challenging and often suboptimal. In this work, we develop a discriminator-free method for training one-dimensional (1D) generative implicit models and subsequently expand this method to accommodate multivariate cases. Our loss function is a discrepancy measure between a suitably chosen transformation of the model samples and a uniform distribution; hence, it is invariant with respect to the true distribution of the data. We first formulate our method for 1D random variables, providing an effective solution for approximate reparameterization of arbitrary complex distributions. Then, we consider the temporal setting (both univariate and multivariate), in which we model the conditional distribution of each sample given the history of the process. We demonstrate through numerical simulations that this new method yields promising results, successfully learning true distributions in a variety of scenarios and mitigating some of the well-known problems that state-of-the-art implicit methods present.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10734829,

title = {Calibration Methods for Alzheimer Disease Detection},

author = {Lorena Gallego-Vi\~{n}ar\'{a}s and Anna Michela-Gaeta and Gerard Pinol-Ripoll and Ferr\'{a}n Barb\'{e} and Pablo M. Olmos and Arrate Mu\~{n}oz-Barrutia},

doi = {10.1109/MLSP58920.2024.10734829},

year  = {2024},

date = {2024-01-01},

booktitle = {2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)},

pages = {1-6},

keywords = {Measurement;Histograms;Accuracy;Sleep;Predictive models;Brain modeling;Electroencephalography;Calibration;Reliability;Alzheimer\'s disease;Alzheimer\'s disease (AD);Deep Neural Networks (DNN);Electro Encephalogram (EEG);Polysomnography (PSG);calibration;confidences},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{inproceedings,

title = {Diffusion X-ray image denoising},

author = {Daniel Sanderson and Pablo Olmos and Carlos Fern\'{a}ndez Del Cerro and Manuel Desco and Monica Abella},

year  = {2024},

date = {2024-01-01},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10627554,

title = {The Data-Driven Radio Frequency Signal Separation Challenge},

author = {Tejas Jayashankar and Binoy Kurien and Alejandro Lancho and Gary C. F. Lee and Yury Polyanskiy and Amir Weiss and Gregory W. Wornell},

doi = {10.1109/ICASSPW62465.2024.10627554},

year  = {2024},

date = {2024-01-01},

booktitle = {2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)},

pages = {53-54},

keywords = {Radio frequency;Knowledge engineering;Source separation;Interference cancellation;RF signals;Neural networks;Modulation;Source separation;interference rejection;machine learning;wireless communication},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sztamfater2024novel,

title = {Novel method for the Computation of In-Orbit Collision Probability by Multilevel Splitting and Surrogate Modelling},

author = {Yannick Sztamfater Garcia and Manuel Sanjurjo Rivo and Joaquin Miguez and Guillermo Escribano},

year  = {2024},

date = {2024-01-01},

booktitle = {AIAA SCITECH 2024 Forum},

pages = {1813},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{RamirezSantamariaScharf-2023-Passivedetectionofrank-oneGaussian,

title = {Passive detection of rank-one Gaussian signals for known channel subspaces and arbitrary noise},

author = {David Ram\'{i}rez and I. Santamar\'{i}a and L. L. Scharf},

doi = {10.1109/ICASSP49357.2023.10094671},

year  = {2023},

date = {2023-01-01},

booktitle = {Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process.},

address = {Rhodes, Greece},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{StantonWangRamirez-2023-Identifiabilityofmulti-channelfactoranalysis,

title = {Identifiability of multi-channel factor analysis},

author = {G. Stanton and H. Wang and David Ram\'{i}rez and I. Santamaria and L. L. Scharf},

year  = {2023},

date = {2023-01-01},

booktitle = {Proc. Asilomar Conf. Signals, Syst. and Computers},

address = {Pacific Grove, USA},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Lancho_2022,

title = {Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals},

author = {Alejandro Lancho and Amir Weiss and Gary C. F. Lee and Jennifer Tang and Yuheng Bu and Yury Polyanskiy and Gregory W. Wornell},

url = {http://dx.doi.org/10.1109/GLOBECOM48099.2022.10001513},

doi = {10.1109/globecom48099.2022.10001513},

year  = {2022},

date = {2022-12-01},

booktitle = {GLOBECOM 2022 - 2022 IEEE Global Communications Conference},

pages = {2296\textendash2302},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Lee_2022,

title = {Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation},

author = {Gary C. F. Lee and Amir Weiss and Alejandro Lancho and Jennifer Tang and Yuheng Bu and Yury Polyanskiy and Gregory W. Wornell},

url = {http://dx.doi.org/10.1109/MLSP55214.2022.9943311},

doi = {10.1109/mlsp55214.2022.9943311},

year  = {2022},

date = {2022-08-01},

booktitle = {2022 IEEE 32nd International Workshop on Machine Learning for Signal Processing (MLSP)},

pages = {1\textendash6},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10052080,

title = {Efficient evaluation of the error probability for pilot-assisted finite-blocklength transmission},

author = {A. Oguz Kislal and Alejandro Lancho and Giuseppe Durisi and Erik G. Str\"{o}m},

doi = {10.1109/IEEECONF56349.2022.10052080},

year  = {2022},

date = {2022-01-01},

booktitle = {2022 56th Asilomar Conference on Signals, Systems, and Computers},

pages = {1038-1044},

keywords = {Fading channels;Computers;Monte Carlo methods;Upper bound;Error probability;Symbols;Channel estimation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9965931,

title = {Second-Order Asymptotics of Hoeffding-Like Hypothesis Tests},

author = {K. V. Harsha and Jithin Ravi and Tobias Koch},

doi = {10.1109/ITW54588.2022.9965931},

year  = {2022},

date = {2022-01-01},

booktitle = {2022 IEEE Information Theory Workshop (ITW)},

pages = {654-659},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{klimovskaia2022signal,

title = {Signal Domain Learning Approach for Optoacoustic Image Reconstruction from Limited View Data},

author = {Anna Klimovskaia and Berkan Lafci and Firat Ozdemir and Neda Davoudi and Xose Luis Dean-Ben and Fernando Perez-Cruz and Daniel Razansky},

url = {https://openreview.net/forum?id=9NOyrfUBtx1},

year  = {2022},

date = {2022-01-01},

booktitle = {Medical Imaging with Deep Learning},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9771953,

title = {Deep Reinforcement Learning for Random Access in Machine-Type Communication},

author = {Muhammad Awais Jadoon and Adriano Pastore and Monica Navarro and Fernando Perez-Cruz},

doi = {10.1109/WCNC51071.2022.9771953},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {2022 IEEE Wireless Communications and Networking Conference (WCNC)},

pages = {2553-2558},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{AArtes20g,

title = {Multinomial Sampling for hierarchical Change-Point Detection},

author = {Lorena Romero-Medrano and P Moreno-Mu\~{n}oz and Antonio Art\'{e}s-Rodr\'{i}guez},

year  = {2021},

date = {2021-10-08},

urldate = {2020-09-21},

booktitle = {Journal of Signal Processing Systems},

keywords = {Bayesian inference, change-point detection (CPD), latent variable models, multinomial likelihoods},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{GargRamirez,

title = {Sparse subspace averaging for order estimation},

author = {V. Garg and David Ram\'{i}rez and Ignacio Santamar\'{i}a},

doi = {10.1109/SSP49050.2021.9513773},

year  = {2021},

date = {2021-07-01},

urldate = {2021-07-01},

booktitle = {Proc. IEEE Work. Stat. Signal Process.},

address = {Rio de Janeiro, Brazil},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2021EGUGA..23.6154P,

title = {Data-driven automatic predictions of avalanche danger in Switzerland},

author = {C. P\'{e}rez-Guill\'{e}n and M. Hendrick and Frank Techel and A. Herwijnen and Michele Volpi and Olevski Tasko and Fernando Perez-Cruz and G. Obozinski and J. Schweizer},

doi = {10.5194/egusphere-egu21-6154},

year  = {2021},

date = {2021-04-01},

urldate = {2021-04-01},

booktitle = {EGU General Assembly Conference Abstracts},

pages = {EGU21-6154},

series = {EGU General Assembly Conference Abstracts},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{virgili2021uncertainty,

title = {Uncertainty Propagation Meeting Space Debris Needs},

author = {Benjamin Bastida Virgili and Jorge Bravo Aguado and Alejandro Cano and Diego Escobar and Stijn S Lemmens and J L\'{o}pez-Santiago and Alberto L\'{o}pez Yela and Pablo M Olmos and Klaus Merz and Joaqu\'{i}n M\'{i}guez and Manuel A V\'{a}zquez},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {8th European Conference on Space Debris},

keywords = {yo},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Ravi-Asilomar2021,

title = {Scaling Laws for Many-Access Channels and Unsourced Random Access},

author = {Jithin Ravi and Tobias Koch},

doi = {10.1109/IEEECONF53345.2021.9723116 address = Pacific Grove, CA, USA},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {2021 55th Asilomar Conference on Signals, Systems, and Computers},

pages = {1482-1487},

note = {Invited},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9287757,

title = {On the computation of marginal likelihood via MCMC for model selection and hypothesis testing},

author = {Fernando Llorente and Luca Martino and David Delgado-G\'{o}mez and J L\'{o}pez-Santiago},

doi = {10.23919/Eusipco47968.2020.9287757},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {2020 28th European Signal Processing Conference (EUSIPCO)},

pages = {2373-2377},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9287359,

title = {Kalman-based nested hybrid filters for recursive inference in state-space models},

author = {Sara P\'{e}rez-Vieites and Joaqu\'{i}n M\'{i}guez},

doi = {10.23919/Eusipco47968.2020.9287359},

year  = {2021},

date = {2021-01-01},

booktitle = {2020 28th European Signal Processing Conference (EUSIPCO)},

pages = {2468-2472},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Tobi20c,

title = {Bursty Wireless Networks of Bounded Capacity},

author = {Grace Villacr\'{e}s and Tobias Koch and Gonzalo Vazquez-Vilar},

doi = {10.1109/ISIT44484.2020.9174034},

year  = {2020},

date = {2020-06-21},

booktitle = {2020 IEEE International Symposium on Information Theory (ISIT)},

pages = {2959-2964},

keywords = {Signal to noise ratio},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Tobi20d,

title = {A High-SNR Normal Approximation for MIMO Rayleigh Block-Fading Channels},

author = {Chao Qi and Tobias Koch},

doi = {10.1109/ISIT44484.2020.9174409},

year  = {2020},

date = {2020-06-21},

booktitle = {2020 IEEE International Symposium on Information Theory (ISIT)},

pages = {2314-2319},

keywords = {Multiple Input Multiple Output (MIMO), Signal to noise ratio},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Tobi20e,

title = {Capacity per Unit-Energy of Gaussian Random Many-Access Channels},

author = {Jithin Ravi and Tobias Koch},

doi = {10.1109/ISIT44484.2020.9174091},

year  = {2020},

date = {2020-06-21},

booktitle = {2020 IEEE International Symposium on Information Theory (ISIT)},

pages = {3025-3030},

keywords = {Gaussian channels},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2020EGUGA..2219564S,

title = {Data assimilation in lake Geneva using the SPUX framework},

author = {Artur Safin and Damien Bouffard and James Runnalls and Fotis Georgatos and Eric Bouillet and Firat Ozdemir and Fernando Perez-Cruz and Jonas \v{S}ukys},

doi = {10.5194/egusphere-egu2020-19564},

year  = {2020},

date = {2020-05-01},

urldate = {2020-05-01},

booktitle = {EGU General Assembly Conference Abstracts},

pages = {19564},

series = {EGU General Assembly Conference Abstracts},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{gvazquez-IZS2020,

title = {On the Error Probability of Optimal Codes in Gaussian Channels under Average Power Constraint},

author = {Gonzalo Vazquez-Vilar},

year  = {2020},

date = {2020-02-01},

booktitle = {2020 International Zurich Seminar on Information and Communication (IZS 2020)},

address = {Zurich, Switzerland},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{zhang2020average,

title = {On the average rate for coded caching with heterogeneous user profiles},

author = {Ciyuan Zhang and Borja Peleato},

year  = {2020},

date = {2020-01-01},

booktitle = {ICC 2020-2020 IEEE International Conference on Communications (ICC)},

pages = {1--6},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ethz-b-000403243,

title = {On the Per-User Probability of Error in Gaussian Many-Access Channels},

author = {Jithin Ravi and Tobias Koch},

year  = {2020},

date = {2020-01-01},

booktitle = {International Zurich Seminar on Information and Communication (IZS 2020)},

pages = {139-143},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{perez2020nested,

title = {A nested hybrid filter for parameter estimation and state tracking in homogeneous multi-scale models},

author = {Sara P\'{e}rez-Vieites and Joaqu\'{i}n M\'{i}guez},

year  = {2020},

date = {2020-01-01},

booktitle = {2020 IEEE 23rd International Conference on Information Fusion (FUSION)},

pages = {1--8},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{norbury2020use,

title = {Use of Actigraphy and Ecological Momentary Assessment to Monitor the Impact of COVID-19 on Mood and Behavior in Psychiatric Outpatients: Social Media and Smartphone App Use Predicts Maintenance of Physical Activity},

author = {Agnes Norbury and Shelley Liu and Maria Luisa Barrigon and Juan Jose Campana-Montes and Lorena Romero-Medrano and Emma Smith and Elizabeth Ramjas and Antonio Art\'{e}s-Rodr\'{i}guez and Enrique Baca-Garcia and Mercedes M Perez-Rodriguez},

year  = {2020},

date = {2020-01-01},

booktitle = {NEUROPSYCHOPHARMACOLOGY},

volume = {45},

number = {SUPPL 1},

pages = {300--300},

organization = {SPRINGERNATURE CAMPUS, 4 CRINAN ST, LONDON, N1 9XW, ENGLAND},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{kim2020sleep,

title = {Sleep Dynamics, Weight, and Appetite in a Prospective Cohort of Psychiatric Patients During COVID-19},

author = {Youngjung Kim and Juan Jose Campa\~{n}a-Montes and Antonio Art\'{e}s-Rodr\'{i}guez and Enrique Baca-Garcia and Mercedes M Perez-Rodriguez},

year  = {2020},

date = {2020-01-01},

booktitle = {NEUROPSYCHOPHARMACOLOGY},

volume = {45},

number = {SUPPL 1},

pages = {254--255},

organization = {SPRINGERNATURE CAMPUS, 4 CRINAN ST, LONDON, N1 9XW, ENGLAND},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{aradillas2020improving,

title = {Improving offline HTR in small datasets by purging unreliable labels},

author = {Jos\'{e} Carlos Aradillas and Juan Jos\'{e} Murillo-Fuentes and Pablo M Olmos},

year  = {2020},

date = {2020-01-01},

booktitle = {2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR)},

pages = {25--30},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{rios2020hidden,

title = {Hidden Markov Models for Activity Detection in Atrial Fibrillation Electrograms},

author = {Gonzalo R\'{i}os-Mu\~{n}oz and Fernando Moreno-Pino and Nina Soto and Pablo M Olmos and Antonio Art\'{e}s-Rodr\'{i}guez and Francisco Fernandez-Aviles and Angel Arenal},

year  = {2020},

date = {2020-01-01},

booktitle = {2020 Computing in Cardiology},

pages = {1--4},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9322143,

title = {On the Design of Generalized LDPC Codes with Component BCJR Decoding},

author = {Yanfang Liu and Pablo M Olmos and David G M Mitchell},

doi = {10.1109/GLOBECOM42002.2020.9322143},

year  = {2020},

date = {2020-01-01},

booktitle = {GLOBECOM 2020 - 2020 IEEE Global Communications Conference},

pages = {1-6},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{leon2020modulation,

title = {Modulation of LED Photo-Luminescence for Underwater Optical Communications},

author = {Walter D Leon-Salas and Xiaozhe Fan and James Hidalgo and Borja Peleato and Pablo J Molina},

year  = {2020},

date = {2020-01-01},

booktitle = {2020 IEEE International Symposium on Circuits and Systems (ISCAS)},

pages = {1--5},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{chang2020coded,

title = {On coded caching for two users with overlapping demand sets},

author = {Chih-Hua Chang and Chih-Chun Wang and Borja Peleato},

year  = {2020},

date = {2020-01-01},

booktitle = {ICC 2020-2020 IEEE International Conference on Communications (ICC)},

pages = {1--6},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{naviadouble,

title = {Double Confidential Federated Machine Learning Logistic Regression for Industrial Data Platforms},

author = {A Navia-V\'{a}zquez and Manuel A V\'{a}zquez and J Cid-Sueiro},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with ICML (FL-ICML) 2020},

keywords = {yo},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Bonilla-EscribanoRamirezArtes-Rodriguez-2020,

title = {Modeling phone call durations via switching Poisson processes with applications in mental health},

author = {P Bonilla-Escribano and David Ram\'{i}rez and Antonio Art\'{e}s-Rodr\'{i}guez},

year  = {2020},

date = {2020-00-01},

booktitle = {Proc. IEEE Int. Work. Machine Learning for Signal Process.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Moreno-MunozRamirezArtes-Rodriguez-2020,

title = {Continual learning for infinite hierarchical change-point detection},

author = {P Moreno-Mu\~{n}oz and David Ram\'{i}rez and Antonio Art\'{e}s-Rodr\'{i}guez},

doi = {10.1109/ICASSP40776.2020.9053853},

year  = {2020},

date = {2020-00-01},

booktitle = {Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process.},

address = {Barcelona, Spain},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{XiaoRamirezSchreier-2020,

title = {A general test for the linear structure of covariance matrices of Gaussian populations},

author = {Y -H Xiao and David Ram\'{i}rez and Peter J Schreier},

doi = {10.1109/ICASSP40776.2020.9053718},

year  = {2020},

date = {2020-00-01},

booktitle = {Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process.},

address = {Barcelona, Spain},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{JMiguez19c,

title = {Multilayer Models of Random Sequences: Representability and Inference via Nonlinear Population Monte Carlo},

author = {Joaqu\'{i}n Miguez and Lucas Lacasa and Jos\'{e} A. Mart\'{i}nez-Ord\'{o}\~{n}ez and In\'{e}s P. Mari\~{n}o},

doi = {10.1109/CAMSAP45676.2019.9022529},

year  = {2019},

date = {2019-12-15},

booktitle = {2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},

keywords = {Markov chains, Multilayer networks, population Monte Carlo, random sequences},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{gvazquez-isit2019,

title = {On the Error Probability of Optimal Codes in Gaussian Channels under Maximal Power Constraint},

author = {Gonzalo Vazquez-Vilar},

year  = {2019},

date = {2019-07-01},

booktitle = {2019 IEEE International Symposium on Information Theory (ISIT 2019)},

address = {Paris, France},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{perez2019second,

title = {Second Order Subspace Statistics for Adaptive State-Space Partitioning in Multiple Particle Filtering},

author = {Sara P\'{e}rez-Vieites and Jordi Vil\'{a}-Valls and M\'{o}nica F Bugallo and Joaqu\'{i}n M\'{i}guez and Pau Closas},

doi = {10.1109/CAMSAP45676.2019.9022449},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

booktitle = {2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},

pages = {609-613},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9049072b,

title = {Finite-Blocklength Approximations for Noncoherent Rayleigh Block-Fading Channels},

author = {Alejandro Lancho and Johan \"{O}stman and Tobias Koch and Gonzalo Vazquez-Vilar},

doi = {10.1109/IEEECONF44664.2019.9049072},

year  = {2019},

date = {2019-01-01},

booktitle = {2019 53rd Asilomar Conference on Signals, Systems, and Computers},

pages = {815-819},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-030-21949-9_21,

title = {Synchrotron X-Ray Phase Contrast Imaging and Deep Neural Networks for Cardiac Collagen Quantification in Hypertensive Rat Model},

author = {Hector Dejea and Christine Tanner and R. Achanta and Marco Stampanoni and Fernando Perez-Cruz and Ender Konukoglu and Anne Bonnin},

editor = {Yves Coudi`ere and Val\'{e}ry Ozenne and Edward Vigmond and Nejib Zemzemi},

isbn = {978-3-030-21949-9},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

booktitle = {Functional Imaging and Modeling of the Heart},

pages = {187--195},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {\"{A}n excessive deposition of collagen matrix in the myocardium has been clearly identified as an indication of the progression towards heart failure. Nevertheless, few studies have been performed for its quantification and most of them use 2D histological images, thus losing valuable encoded 3D information. In this study, several biopsies of areas of the left ventricle from age-matched spontaneously hypertensive rats and Wistar Kyoto rats were imaged using synchrotron radiation-based X-ray phase contrast imaging. Then, an optimized deep neural network was used for automatic image segmentation in order to assess collagen fraction differences between models as well as its age dependency. The results show a general increase in the collagen percentage in the hypertensive model and for older rats. Such tendency is comparable with the reports found in the literature. Therefore, this proof of concept shows that synchrotron imaging in combination with deep neural networks is a powerful tool for the investigation and quantification of cardiac microstructures."},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{BonillaEscribano2019MixturesOH,

title = {Mixtures of Heterogeneous Poisson Processes for the Assessment of e-Social Activity in Mental Health},

author = {P Bonilla-Escribano and David Ram\'{i}rez and Antonio Art\'{e}s-Rodr\'{i}guez},

year  = {2019},

date = {2019-01-01},

abstract = {This work introduces a novel method to assess the social activity maintained by psychiatric patients using information and communication technologies. In particular, we jointly model using point processes the e-social activity patterns from two heterogeneous sources: the usage of phone calls and social and communication apps. We propose a nonhomogeneous Poisson mixture model with periodic (circadian) intensity function using a truncated Fourier series expansion, which is inferred using a trust-region algorithm, and it is able to cope with the different daily patterns of a person. The analysis of the usage of phone calls and social and communication apps of a cohort of 164 patients reveals that 25 patterns suffice to characterize their daily behavior.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{8849751,

title = {Capacity per Unit-Energy of Gaussian Many-Access Channels},

author = {Jithin Ravi and Tobias Koch},

year  = {2019},

date = {2019-01-01},

booktitle = {2019 IEEE International Symposium on Information Theory (ISIT)},

pages = {2763-2767},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{8849659,

title = {Saddlepoint Approximations for Noncoherent Single-Antenna Rayleigh Block-Fading Channels},

author = {Alejandro Lancho and Johan \"{O}stman and Giuseppe Durisi and Tobias Koch and Gonzalo Vazquez-Vilar},

year  = {2019},

date = {2019-01-01},

booktitle = {2019 IEEE International Symposium on Information Theory (ISIT)},

pages = {612-616},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}