Naila Murray's guest appearances

Naila Murray

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Underrated ML

The Caribbean Data Science Podcast

Sebastian Ruder

Stephen Merity

Scott Clark

Celeste Kidd

Dennis Mortensen

Rob Walker

Sanmi Koyejo

Chelsea Finn

Dario Amodei

Jianxiong Xiao

Kate Darling

Jason Holmberg

Lotte Bransen

Christopher Berner

David Spiegelhalter

OwlTail

This week we are joined by Naila Murray. Naila obtained a B.Sc. in Electrical Engineering from Princeton University in 2007. In 2012, she received her PhD from the Universitat Autonoma de Barcelona, in affiliation with the Computer Vision Center. She joined NAVER LABS Europe (then Xerox Research Centre Europe) in January 2013, working on topics including fine-grained visual categorization, image retrieval, and visual attention. From 2015 to 2019 she led the computer vision team at NLE. She currently serves as NLE's director of science. She serves/served as area chair for ICLR 2018, ICCV 2019, ICLR 2019, CVPR 2020, ECCV 2020, and programme chair for ICLR 2021. Her research interests include representation learning and multi-modal search.We discuss using sparse pairwise comparisons to learn a ranking function that is robust to outliers. We also take a look at using generative models in order to utilise once inaccessible datasets.Underrated ML Twitter: https://twitter.com/underrated_mlNaila Murray Twitter: https://twitter.com/NailaMurrayPlease let us know who you thought presented the most underrated paper in the form below: https://forms.gle/97MgHvTkXgdB41TC8Links to the papers:"Interestingness Prediction by Robust Learning to Rank" [paper]"Generative Models for Effective ML on Private Decentralized datasets" - [paper]

This week we are joined by Naila Murray. Naila obtained a <a href="http://B.Sc" rel="nofollow" target="_blank">B.Sc</a>. in Electrical Engineering from Princeton University in 2007. In 2012, she received her PhD from the Universitat Autonoma de Barcelona, in affiliation with the Computer Vision Center. She joined NAVER LABS Europe (then Xerox Research Centre Europe) in January 2013, working on topics including fine-grained visual categorization, image retrieval, and visual attention. From 2015 to 2019 she led the computer vision team at NLE. She currently serves as NLE's director of science. She serves/served as area chair for ICLR 2018, ICCV 2019, ICLR 2019, CVPR 2020, ECCV 2020, and programme chair for ICLR 2021. Her research interests include representation learning and multi-modal search. We discuss using sparse pairwise comparisons to learn a ranking function that is robust to outliers. We also take a look at using generative models in order to utilise once inaccessible datasets. Underrated ML Twitter: <a href="https://twitter.com/underrated_ml" rel="nofollow" target="_blank">https://twitter.com/underrated_ml</a> Naila Murray Twitter: <a href="https://twitter.com/NailaMurray" rel="nofollow" target="_blank">https://twitter.com/NailaMurray</a> Please let us know who you thought presented the most underrated paper in the form below: <a href="https://forms.gle/97MgHvTkXgdB41TC8" rel="nofollow" target="_blank">https://forms.gle/97MgHvTkXgdB41TC8</a> Links to the papers:"Interestingness Prediction by Robust Learning to Rank" [<a href="https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/6748/GONG%20Interestingness%20prediction%20by%20robust%202014%20Accepted.pdf?sequence=2" rel="nofollow" target="_blank">paper</a>]"Generative Models for Effective ML on Private Decentralized datasets" - [<a href="https://arxiv.org/pdf/1911.06679.pdf" rel="nofollow" target="_blank">paper</a>]

Naila Murray - Interestingness predictions and getting to grips with data privacy

In this episode of our Deep Learning Indaba series, we’re joined by Naila Murray, Senior Research Scientist and Group Lead in the computer vision group at Naver Labs Europe.Naila presented at the Indaba on computer vision. In this discussion, we explore her work on visual attention, including why visual attention is important and the trajectory of work in the field over time. We also discuss her paper  “Generalized Max Pooling,” and much more!For the complete show notes, visit twimlai.com/tal

In this episode of our Deep Learning Indaba series, we’re joined by Naila Murray, Senior Research Scientist and Group Lead in the computer vision group at Naver Labs Europe. Naila presented at the Indaba on computer vision. In this discussion, we explore her work on visual attention, including why visual attention is important and the trajectory of work in the field over time. We also discuss her paper  “Generalized Max Pooling,” and much more! For the complete show notes, visit <a href="http://twimlai.com/tal" rel="nofollow" target="_blank">twimlai.com/tal</a>

Learning Representations for Visual Search with Naila Murray - TWiML Talk #190