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Tag:

Machine Learning

WEDNESDAY

Track 1

10.00 to 10.50

Staying Safe in the AI Future

Cassie Kozyrkov - Google

14.50 to 15.30

Using Graphs for AI and ML with no BS

Jim Webber - Neo4J

16.20 to 17.00

Delta Lake: Reliability and Data Quality for Data Lakes and Apache Spark

Michael Armbrust - Databricks

17.05 to 17.45

From trained models to machine learning systems

William Benton - Red Hat

Track 3

13.20 to 14.00

Data Intelligence driving vehicle electrification forward

Jorge González - Geotab

16.20 to 17.00

Natural Language Generation: Explaining the unexplainable AI?

Alberto Bugarín - University of Santiago de Compostela

José María Alonso Moral - University of Santiago de Compostela

Track 4

12.35 to 13.15

Time-Efficient Aircraft Fault Isolation Procedures with NLP techniques

Miguel Martín Acosta - Airbus Defense and Space

Rocío Martín Martín - Airbus Defense and Space

14.05 to 14.45

Icaro project: Predicting Biosphere Behavior by using ML Cloud Engine

Moisés Martínez - Sngular

Inés Huertas - The Sideways Project

15.35 to 16.15

An Image is Worth a Thousand Words (Vol. 2)

David López Recio - Minsait

16.20 to 17.00

Fairing: Bringing Kubernetes for Data Scientists

Karthik Ramasamy - Google

Vaibhav Singh - Google

17.05 to 17.45

Operationalizing Data Science using the Azure stack

María Medina - Microsoft

17.50 to 18.30

Generative models (Gaussian Mixture Models) for images and time series

Alok N Singh - IBM

Track 5

11.00 to 11.40

Fix it before it Breaks: Incremental Learning for Predictive Maintenance

Peter Webb - MathWorks

Lucio Cetto - MathWorks

11.45 to 12.25

Fashion Recommendations at Scale, lessons learned

Humberto Corona - Zalando

14.50 to 15.30

A Recommender Dart straight to DIA’s Traditional Coupon Assignment Heart

Maite Álvarez Díaz - DIA Group

Guillermo Fernández Rodríguez - BBVA Next Technologies

15.35 to 16.15

#oneJourneyWiser

Carlos Herrera - Cabify

17.50 to 18.30

The future was this: Serverless face recognition in real-time video

Javier Ramírez - Amazon Web Services

THURSDAY

Track 2

10.55 to 11.35

Using Neo4j and Machine Learning to Create a Decision Engine

Timothy Ward - CluedIn

13.10 to 13.50

Disentangling risks, activity and performance through US corporate reports

Tomasa Rodrigo - BBVA Research

14.40 to 15.20

How I won the Alibaba self-driving LIDAR point cloud segmentation competition

Andrés Torrubia - fixr.com

15.25 to 16.05

Unpacking AutoML

Paco Nathan - Derwen

Track 3

14.40 to 15.20

xAI for unsupervised ML in anomaly detection. Use case of LUCA Comms

Alberto Barbado González - Telefónica

Álvaro Sánchez Pérez - Telefónica

15.25 to 16.05

Machine Learning for federated privacy-preserving scenarios

Roberto Díaz Morales - Tree Technology

Track 4

11.40 to 12.20

Would you trust your model with your life? Research vs. reality in AI

Heather Gorr - MathWorks

14.40 to 15.20

Omni-Channel Customer-Centric Strategies in a Modern Architecture

Luis García Castro - ING

Pablo Ruiz Subira - ING

Track 5

14.40 to 15.20

Bayesian Voice Emotion Detection Applied to Robotics: Adding Uncertainty

Rubén Martínez Sánchez - Datahack

15.25 to 16.05

Safety Experience Engine (SEE). Content Qualification Cloud Tool

Pedro Ventura - PRISA

Lander Trapaga Corral - Minsait