Electronic proceedings author index

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Mirko Polato
  • No papers found
Mirko Polato
  • ESANN 2021 - Privacy-Preserving Kernel Computation For Vertically Partitioned Data [Details]
Mirko Polato
  • ESANN 2022 - Bayes Point Rule Set Learning [Details]
  • ESANN 2024 - FedHP: Federated Learning with Hyperspherical Prototypical Regularization [Details]
  • ESANN 2024 - Machine learning in distributed, federated and non-stationary environments - recent trends [Details]
  • ESANN 2024 - Vision Language Models as Policy Learners in Reinforcement Learning Environments [Details]
Mirko Polato
  • ESANN 2016 - Kernel based collaborative filtering for very large scale top-N item recommendation [Details]
  • ESANN 2018 - Boolean kernels for interpretable kernel machines [Details]
  • ESANN 2018 - The minimum effort maximum output principle applied to Multiple Kernel Learning [Details]
Arturs Polis
  • ESANN 2021 - A Relational Model for One-Shot Classification [Details]
Kai Polsterer
  • ESANN 2014 - Speedy greedy feature selection: Better redshift estimation via massive parallelism [Details]
  • ESANN 2015 - Autoencoding time series for visualisation [Details]
Kai L. Polsterer
  • ESANN 2024 - Automatic Miscalibration Diagnosis: Interpreting Probability Integral Transform (PIT) Histograms [Details]
  • ESANN 2024 - Positive and Scale Invariant Gaussian Process Latent Variable Model for Astronomical Spectra [Details]
Kai Lars Polsterer
  • ESANN 2016 - Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs [Details]
  • ESANN 2017 - Uncertain photometric redshifts via combining deep convolutional and mixture density networks [Details]
Marios Polycarpou
  • ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
Georg Pölzlbauer
  • ESANN 2005 - Graph projection techniques for Self-Organizing Maps [Details]
Héctor Pomares
  • ESANN 2004 - MultiGrid-Based Fuzzy Systems for Time Series: Forecasting: Overcoming the curse of dimensionality [Details]
  • ESANN 2009 - Applying Mutual Information for Prototype or Instance Selection in Regression Problems [Details]
Héctor Pomares
  • ESANN 2004 - Soft-computing techniques for time series forecasting [Details]
H. Pomares
  • ESANN 1998 - What are the main factors involved in the design of a Radial Basis Function Network? [Details]
Filippo Pompili
  • ESANN 2013 - ONP-MF: An Orthogonal Nonnegative Matrix Factorization Algorithm with Application to Clustering [Details]
Tossapol Pomsuwan
  • ESANN 2020 - Adapting Random Forests to Cope with Heavily Censored Datasets in Survival Analysis [Details]
A. Poncet
  • ESANN 1998 - Selecting among candidate basis functions by crosscorrelations [Details]
Massimiliano Pontil
  • ESANN 2019 - PAC-Bayes and Fairness: Risk and Fairness Bounds on Distribution Dependent Fair Priors [Details]
M. Pontil
  • ESANN 1999 - From regression to classification in support vector machines [Details]
  • ESANN 1999 - Support vector machines vs multi-layer perceptrons in particle identification [Details]
  • ESANN 2003 - On different ensembles of kernel machines [Details]
  • ESANN 2003 - Reproducing kernels and regularization methods in machine learning [Details]
Filip Ponulak
  • ESANN 2006 - Generalization properties of spiking neurons trained with ReSuMe method [Details]
Danut Ovidiu Pop
  • ESANN 2017 - Fusion of Stereo Vision for Pedestrian Recognition using Convolutional Neural Networks [Details]
  • ESANN 2019 - Improving Pedestrian Recognition using Incremental Cross Modality Deep Learning [Details]
Mikhail Popov
  • ESANN 2020 - Anomaly Detection Approach in Cyber Security for User and Entity Behavior Analytics System [Details]
Mario Porrmann
  • ESANN 2012 - gNBXe -- a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps [Details]
M. Porrmann
  • ESANN 2002 - A reconfigurable SOM hardware accelerator [Details]
Filippo Portera
  • ESANN 2004 - a preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks [Details]
Iago Porto-Díaz
  • ESANN 2014 - Modeling consumption of contents and advertising in online newspapers [Details]
Michael Potter
  • No papers found
Michael Potter
  • ESANN 2022 - Dynamics-aware Representation Learning via Multivariate Time Series Transformers [Details]
Alejandro Pozas-Kerstjens
  • ESANN 2020 - Understanding and improving unsupervised training of Boltzman machines [Details]
Alexei Pozdnoukhov
  • ESANN 2008 - GeoKernels: modeling of spatial data on geomanifolds [Details]
Maria Prapopoulou
  • ESANN 2010 - The Application of Gaussian Processes in the Prediction of Percutaneous Absorption for Mammalian and Synthetic Membranes [Details]