Recommended videolectures selected by EDSA. The videolectures are from world-renowned experts on data science related topics. Click on the image or the titles to view the videolecture on

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2018: March
2017: MarchMayJuneJuly
2016: AprilJuneAugustSeptemberOctoberNovember

March 2018

Neural Networks

Recurrent Neural Networks (RNNs)

Blockchain Enabled Privacy Audit Logs

Applied semantics: beyond the catalog

July 2017

Reinforcement Learning

Dr. Joelle Pineau – Reinforcement Learning

June 2017

Machine Learning

Dr. Doina Precup – Machine Learning

May 2017

Methods for Intrinsic Evaluation of Links in the Web of Data

Cristina Sarasua – Methods for Intrinsic Evaluation of Links in the Web of Data

Limits of the current state of Artificial Intelligence for Law

Marko Grobelnik – Limits of the current state of Artificial Intelligence for Law

March 2017

Introduction to Complexity Science

Professor Peter Sloot – Introduction to Complexity Science

November 2016

Dr. Marc Mézard – Data science and the curse of phase transitions

October 2016

Dr Hiroaki Kitano

Dr. Hiroaki Kitano – Artificial Intelligence to Win the Nobel Prize and Beyond: Creating the Engine for Scientific Discovery

Dr Kathleen McKeown

Dr. Kathleen McKeown – At the Intersection of Data Science and Language

Dr Christian Bizer

Professor Christian Bizer – Is the Semantic Web what we expected? Adoption Patterns and Content-driven Challenges

Dr Petar Ristoski

Dr. Petar Ristoski – RDF2Vec: RDF Graph Embeddings for Data Mining

September 2016

Johannes Balle

Dr. Johannes Balle – Density Modeling of Images Using a Generalized Normalization Tansformation

Jennifer Chayes

Jennifer Chayes – Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks

Filip Ilievski

Professor Filip Ilievski – LOTUS: Adaptive Text Search for Big Linked Data

Nando de Freitas

Professor Nando de Freitas – Learning to Learn and Compositionality with Deep Recurrent Neural Networks

Andrei Broder

Dr. Andrei Broder – Is Deep Learning the New 42?

August 2016

Nurali Virani

Nurali Virani – Sequential Hypothesis Tests for Markov Models of Time-Series Data

June 2016

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Professor Jose Bento Ayres Pereira – Learning Networks of Stochastic Differential Equations

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Dr. Caterina De Bacco – A Matrix Product Algorithm for the Far-From-Equilibrium Evolution of Dynamical Processes on Networks

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Dr. Graham Taylor – Learning Multi-Scale Temporal Dynamics with Recurrent Neural Networks

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Dr. Ludovica Bachschmid-Romano – Inference in Kinetic Ising Models: Mean-Field and Bayes Estimators

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Professor Andrea Montanari – Information-Theoretic Bounds on Learning Network Dynamics

April 2016

Yann LeCun

Professor Yann LeCun – It´s Learning All the Way Down

David Lowe
Professor David Lowe – Borrowing New Ideas from Human Vision

Stephen P. Boyd
Professor Stephen P. Boyd – Convex Optimization with Abstract Linear Operators