Machine Learning Group

Temporada 2020/2021

Track on Machine Learning with Graphs (editions 2019 and 2021)

Fecha Aula HoraPonenteTítuloMaterial
16/06/2021Online10:30-12:0019. Applications of Graph NNVideo
09/07/2021Online10:30-12:0018. Limitations of Graph NNsVideo
02/07/2021Online10:30-12:0017. Reasoning over Knowledge GraphsVideo
25/06/2021Online10:30-12:0016. Network EvolutionVideo
18/06/2021Online10:30-12:0015. Outbreak Detection in NetworksVideo
11/06/2021Online10:30-12:0014. Influence Maximization in NetworksVideo
04/06/2021Online10:30-12:0013. Probabilistic Contagion and Models of InfluenceVideo
25/05/2021Online10:30-12:0012. Network Effects and Cascading BehaviorVideo + homework
18/05/2021Online10:30-12:0011. Link Analysis. PageRankVideo
11/05/2021Online10:30-12:0010. Deep Generative Models for GraphsVideo
04/05/2021 Online10:30-12:009. Graph NN Representations with Pythorch GeometricVideo, notebook
27/04/2021Online10:30-12:008. Graph NN RepresentationsVideo, nb2021
20/04/2021 Online10:30-12:007. Graph Representation LearningVideo
13/04/2021Online10:30-12:006. Message Passing and Node ClassificationVideo, homework
06/04/2021 Online10:30-12:005. Spectral ClusteringVideo
23/03/2021Online10:30-12:004. Community Structure in NetworksVideo
16/03/2021Online10:30-12:003. Motifs and Structural Roles In NetworksVideo
09/03/2021Online10:30-12:00 Dockers
02/03/2021 Online10:30-12:002. Properties of Networks and Random Graph ModelsVideo + homework
23/02/2021Offline10:30-12:001. Introduction. Structure of GraphsVideo + homework

Temporada 2018/2019

10/06/2019 4.2.E039:40Carlos SevillaBayesian CCA
27/05/2019 42E029:40Simón RocaContextual String Embeddings for Sequence LabelingURL
29/04/2019 40B01A9:40Jesús CidPyTorch (6): Word-embeddings
01/03/2018 40B01A9:40Óscar GarcíaPyTorch (5): RNN, LSTM.
18/03/2018 42E029:40Simón RocaReading Tea Leaves: How Humans Interpret Topic ModelsSlides
04/03/2019 42E029:40Lorena ÁlvarezPyTorch (4): Image Style Transfer Using Convolutional Neural Networks
12/02/2019 41E029:40Carlos SevillaPyTorch (3):
05/02/2019 41E029:40Jesús CidOnline Passive-Agressive Algorithms
22/01/2019 40E029:40Ángel NaviaPyTorch (2) (y II)
15/01/2019 40E029:40Jerónimo Arenas PyTorch (2):
20/12/2018 42E009:40Luis Muñoz GonzálezAdversarial LearningSlides1, slides2
11/12/2018 41E029:40Óscar GarcíaGenerative Adversarial Nets
27/11/2018 41E029:40Manuel VázquezPyTorch (1):
20/11/2018 40E069:40Lorena ÁlvarezDropout: A Simple Way to Prevent Neural Networks from OverfittingSlides

Temporada 2017/2018

27/06/2018 4.0.D019:40Simón RocaA Little Survey on Traditional and Current Word and Sentence EmbeddingsSlides
20/06/2018 4.0.E069:40Carlos SevillaParsimonious CCA for Biomarker Design: Characterization of Mental Disorders
13/06/2018 4.0.E059:40Pablo Martínez[DL] 20. Deep Generative Models
05/06/2018 7.2.J049:40Luis AzpicuetaDetección Automática de las Diferencias Perceptuales entre Respuestas Impulsivas de Recintos
28/05/2018 4.2.E029:40Ángel Navia Privacy Preserving Machine Learning
21/05/2018 4.2.E029:40Jesús Cid[DL] 19. Approximate InferenceSlides
14/05/2018 4.2.E029:40Simón RocaUnveiling Hidden Semantic Structures of Corpora Using Topic Models
07/05/2018 4.2.E029:40Jerónimo Arenas[DL] 18. Confronting the Partition FunctionSlides
23/04/2018 4.2.E029:40Jesús Fernández BesQuantification of Physiological Cardiac Variability using Adaptive Signal Processing Techniques
16/04/2018 4.2.E029:40Adil OmariDeep Residual Learning for Image Recognition
09/04/2018 4.2.E029:40Vanessa Gómez[DL] 17. Monte Carlo Methods
19/03/2018 4.2.E029:40Óscar García Worm-level Control through Search-based Reinforcement Learning
12/03/2018 4.2.E029:40Fernando de la CalleDeep learning methods for Automatic Speech RecognitionarXiv, arXiv
05/03/2018 4.2.E029:40Lorena Álvarez[DL] 16. Structured Probabilistic Models for Deep LearningSlides
19/02/2018 4.2.E029:40Jesús CidAlgorithms for recycling weakly labeled datasets
12/02/2018 4.2.E029:40Carlos Sevilla[DL] 15. Representation Learning
05/02/2018 4.2.E029:40Pablo Martínez[DL] 14. Autoencoders
01/02/2018 4.2.E029:40Luis AzpicuetaHead-Related Transfer Function (HRTF) + Machine Learning
22/01/2018 4.2.E029:40Manuel Vázquez[DL] 13. Linear Factor Models
17/01/2018 4.1.E029:40Jerónimo ArenasRandom Walk Graph-based SemiSupervised Classification Slides
10/01/2018 4.1.E029:40Ángel Navia[DL] 10. Sequence Modelling: Recurrent and Recursive NetsNB, Slides
29/11/2017 4.2.E029:40Vanessa GómezBayesian Canonical Correlation AnalysisNotes
22/11/2017 4.2.E029:40Simón Roca[DL] 9. Convolutional Networks
15/11/2017 4.2.E029:40Lorena ÁlvarezSemi-supervised learningSlides
08/11/2017 4.2.E029:40Adil Omari[DL] 7. Regularization for Deep Learning and 8. Optimization for Training Deep Models
31/10/2017 4.0.E059:40Diego Rojo Text Categorization from Category Names
18/10/2017 4.2.E029:40Óscar García[DL] 6. Deep Feedforward Networks
20/09/2017 4.2.E029:40Preparatory session: content of the next talks.

Temporada 2016/2017

19/07/20177.1.J039:30Jesús Cid-SueiroPSBI (4): Scaling Variational Mean Field Algorithms
12/07/20174.2.E029:30Abdel MoujahidThe Metabolic Cost of Neuronal Activity
04/07/20174.2.E029:30Pablo Martínez-OlmosPSBI (3): Parallel and distributed MCMC
29/06/20174.2.E029:30Manuel Vázquez-LópezPSBI (2): MCMC with data subsets Slides
20/06/20174.2.E029:30Luis AzpicuetaMachine Learning Methods to Predict Diabetes Complications
14/06/20174.2.E029:30Jerónimo Arenas-GarcíaPatterns of Scalable Bayesian Inference (1): Background Slides, Notes
07/06/20177.1.J029:30Ángel Navia-VázquezNatural Language Processing
31/05/20174.2.E029:30Vanessa Gómez-VerdejoBuilding my Internet Search Engine: Scrapy and Lucene Slides and code
17/05/20174.2.E029:30Simón Roca-SoteloTopic Models and Word Embeddings Slides
10/05/20174.2.E029:30Lorena Álvarez Pérez Training neural networks classifiers through Bayes risk minimization using Parzen windows
03/05/20174.2.E029:30Adil Omari Deep Neural Networks for Wind and Solar Energy Prediction pdf
26/04/20174.2.E029:30Diego Rojo García Visualización en Python con Bokeh
19/04/20174.2.E029:30Jesús Cid-SueiroConvex Optimization (Cap 11: Interior Point Methods)
05/04/20174.2.E029:30Óscar García-Hinde Neo4j Slides, Tutorial
29/03/20174.2.E029:30Henry NavarroConvex Optimization (Cap 10: Equality Constrained Minimization)
22/03/20174.2.E029:30Jerónimo Arenas-GarcíaSQL ppt, csv
15/03/20174.2.E029:30Ángel Navia-VázquezConvex Optimization (Cap 9: Unconstrained Minimization)
01/03/20174.2.E029:30Jesús Cid-SueiroConvex Optimization (Cap 8: Geometric Problems)
22/02/20174.2.E029:30Vanessa Gómez-Verdejo Spark with Dataframes
15/02/20174.2.E029:30Luis AzpicuetaGoogle Fusion Tables
08/02/20174.2.E029:30Simón Roca-SoteloConvex Optimization (Cap 7: Statistical Estimation)
01/02/20174.2.E029:30Lorena Álvarez-Pérez Qlik
25/01/2017 4.2.E029:30Abdel Moujahid(1) A Nonlinear Dynamic Approach to Mouse Behavior Classification, and (2) Object Detection based on Community Identification in Graphs slides
18/01/2017 4.0.E049:30Oscar García-HindeConvex Optimization (Cap 6: Approximation and Fitting)
11/01/2017 4.0.E049:30Henry NavarroTableau SW
21/12/2016 4.2.E029:45Fernando GarcíaMachine Learning en el Tratamiento de la Diabetes Tipo 1
14/12/2016 4.0.D0112:00Miguel Lázaro Hierarchical Compositional Feature Learning
12/12/2016 4.0.D0112:00Darío GarcíaML & AI @ FB
23/11/2016 4.2.E029:30Jerónimo Arenas-GarcíaConvex Optimization (Cap 5: Duality (II))
16/11/20164.2.E039:30Manuel Vázquez-LópezConvex Optimization (Cap 5: Duality (I))
09/11/2016 4.2.E029:30Ángel Navia-Vázquez Carto
02/11/2016 4.2.E029:30Sergio Muñoz-RomeroConvex Optimization (Cap 4: Convex Optimization Problems)
26/10/2016 4.2.E029:30Jesús Cid-Sueiro Gephi Tutorial
19/10/2016 4.2.E029:30Luis AzpicuetaConvex Optimization (Cap. 3: Convex Functions)
07/10/2016 4.2.E039:30Vanessa Gómez VerdejoConvex Optimization (Cap. 2: Convex Sets)

Temporada 2015/2016

21/06/2016 4.1.E02 11:00Juan José ChoquehuancaGenerative Adversarial Nets pdf
14/06/2016 4.1.E02 11:00Óscar García-HindeConsistent Algorithms for Clustering Time Seriespdf
07/06/2016 7.2.H01 9:30Henry NavarroCross Collection Topic Models pdf
31/05/2016 4.2.E02 9:30Raúl Moreno-SalinasAn Introduction to Symbolic Regression
17/05/2016 4.2.E03 9:40Jerónimo Arenas-GarcíaGaussian Processes for Big Data pdf
10/05/2016 4.2.E03 9:30Ángel Navia-VázquezOverview of Apache Flink: Next-Gen Big Data Analytics Framework
03/05/2016 4.2.E03 9:30Sergio Muñoz-RomeroTowards a neocortex-inspired machine learningpdf, html
19/04/2016 4.2.E03 9:30Jesús Cid-SueiroA survey on Sentiment Analysispdf
12/04/2016 4.2.E03 9:30Luis AzpicuetaNoise pollution predition: noise maps + machine learningpdf
05/04/2016 4.2.E03 9:30Vanessa Gómez-VerdejoA Survey on Transfer Learning pdf
08/03/2016 4.2.E03 9:30Juan José ChoquehuancaSpectral Representations for Convolutional Neural Nets NIPS2015
01/03/2016 4.2.E03 9:30Oscar García-HindeFeature Selection in Solar Radiation Prediction Using Bootstrapped SVRs pdf
23/02/2016 4.2.E03 9:30Henry NavarroThe Tie Decay Problem in Social Networks: Why Do People Stop Calling?
16/02/2016 4.2.E03 9:30Raúl Moreno-SalinasDisruption Prediction in Nuclear Fusion Devices Art1 , Art2 , Art3 , Thesis
09/02/2016 4.2.E03 9:30Jesús Fernández-Bes Introduction to Convolutional Networks using TensorFlow web
01/02/2016 4.0.E02 12:00Jerónimo Arenas-GarcíaBDAS (Lab4): Machine Learning with Apache Spark
20/01/2016 4.2.E03 9:30Ángel Navia-VázquezBDAS (L7+L8+Lab3): Data Quality, Exploratory Analysis and Machine Learning (y 2)
13/01/2015 4.0.E029:30Ángel Navia-VázquezBDAS (L7+L8+Lab3): Data Quality, Exploratory Analysis and Machine Learning
16/12/2015 4.0.E029:30Sergio Muñoz-RomeroBDAS (L5+L6+Lab2): Data Management PySpark pictures
09/12/2015 4.0.E029:30Jesús Cid-SueiroBDAS (Lab1): Introduction to Apache Spark
02/12/2015 4.0.E029:30Luis AzpicuetaBDAS (L3+L4): Introduction to Apache Spark
25/11/2015 4.0.E029:30Rocío Arroyo-VallesBig Data with Apache Spark (L1+L2): Introduction and SW setup Slides
18/11/2015 4.0.E029:30Vanessa Gómez VerdejoHadoop and Map Reduce for Dummies

Temporada 2014/2015

06/07/2015 4.2.E03 11:00Oscar García HindeA.Nguyen, J. Yosinski, J. Clune, “Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images”pdf
22/06/2015 4.2.E03 11:00Jerónimo Arenas-GarcíaCollapsed Gibbs Sampling for Latent Dirichlet Allocation on Sparkpdf
19/06/2015 4.0.E04 12:00Miguel Lázaro GredillaTowards Human-Level AIVicarious
10/06/2015 7.1.H01 10:00Jesús Fernández-Bes Algorithms for Energy-Efficient Adaptive Wireless Sensor NetworksTesis
01/06/2015 4.2.E03 12:00Mrityunjoy ChakrabortySparse Distributed Estimation via Heterogeneous Diffusion Adaptive Networks
25/05/2015 4.2.E03 11:00Ángel Navia-VázquezProcesado en array: núcleos y aproximación geométricadoi1, doi2, tutorial1, tutorial2,
11/05/2015 4.2.E03 11:00Sergio Muñoz-RomeroAnálisis multivariante: soluciones eficientes e interpretablesTesis
27/04/2015 4.2.E03 11:00Jesús Cid-SueiroThe U/P assignment problem for lifting transforms on graphs
23/04/2015 4.2.E02 10:30Vanessa Gómez-Verdejo* Model Predictive Regulationpdf
13/04/20154.2.E0311:00Luis Azpicueta* Battery Storage System sizing in distribution feeders with distributed photovoltaic systemsdoi
23/03/20154.0.E0511:00Sergio Muñoz-Romero* Economic viability of energy storage systems based on price arbitrage potential in real-time U.S. electricity marketsdoi
16/03/20154.0.E0511:00Jesús Fernández-Bes* Sizing and Optimal Operation of Battery Energy Storage System for Peak Shaving Applicationdoi
11/03/20152.1.C0811:00Rocío Arroyo-Valles* Stochastic Optimal Control of the Storage System to Limit Ramp Rates of Wind Power Outputdoi
03/03/20154.0.E0414:00Oscar García Hinde * Analysis of battery storage utilization for load shifting and peak smoothing on a distribution feeder in New Mexicodoi

* Las sesiones del Smart-Grid track se han organizado de acuerdo con el documento de referencia elaborado por Manel y Vanessa, que podéis encontrar aquí

Pasadas ediciones


Son o han sido participantes regulares de este foro en algún momento:

  • Oscar García
  • Emilio Parrado
  • Jesús Fernández
  • Vanessa Gómez
  • Jesús Cid
  • Angel Navia
  • Jerónimo Arenas
  • Sergio Muñoz
  • Luis A. Azpicueta
  • Rocío Arroyo
  • Miguel Lázaro
  • Manel Martínez
  • Harold Molina
  • Saúl Blanco
  • Bijit Kumar
  • Emilio Ortiz
  • Roberto Díaz
  • Luis Muñoz
  • Francisco Valverde