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 videolectures.net.
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2018: March
2017: March – May – June – July
2016: April – June – August – September – October – November
March 2018
Neural Networks
Recurrent Neural Networks (RNNs)
Blockchain Enabled Privacy Audit Logs
Applied semantics: beyond the catalog
July 2017
Dr. Joelle Pineau – Reinforcement Learning
June 2017
Dr. Doina Precup – Machine Learning
May 2017
Cristina Sarasua – Methods for Intrinsic Evaluation of Links in the Web of Data
Marko Grobelnik – Limits of the current state of Artificial Intelligence for Law
March 2017
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 – Artificial Intelligence to Win the Nobel Prize and Beyond: Creating the Engine for Scientific Discovery
Dr. Kathleen McKeown – At the Intersection of Data Science and Language
Professor Christian Bizer – Is the Semantic Web what we expected? Adoption Patterns and Content-driven Challenges
Dr. Petar Ristoski – RDF2Vec: RDF Graph Embeddings for Data Mining
September 2016
Dr. Johannes Balle – Density Modeling of Images Using a Generalized Normalization Tansformation
Jennifer Chayes – Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks
Professor Filip Ilievski – LOTUS: Adaptive Text Search for Big Linked Data
Professor Nando de Freitas – Learning to Learn and Compositionality with Deep Recurrent Neural Networks
Dr. Andrei Broder – Is Deep Learning the New 42?
August 2016
Nurali Virani – Sequential Hypothesis Tests for Markov Models of Time-Series Data
June 2016
Professor Jose Bento Ayres Pereira – Learning Networks of Stochastic Differential Equations
Dr. Caterina De Bacco – A Matrix Product Algorithm for the Far-From-Equilibrium Evolution of Dynamical Processes on Networks
Dr. Graham Taylor – Learning Multi-Scale Temporal Dynamics with Recurrent Neural Networks
Dr. Ludovica Bachschmid-Romano – Inference in Kinetic Ising Models: Mean-Field and Bayes Estimators
Professor Andrea Montanari – Information-Theoretic Bounds on Learning Network Dynamics
April 2016
Professor Yann LeCun – It´s Learning All the Way Down
Professor David Lowe – Borrowing New Ideas from Human Vision
Professor Stephen P. Boyd – Convex Optimization with Abstract Linear Operators