AI Institute “Geometry of Deep Learning” 2019 [Day 3 | Session 1]
- Piotr Indyk | MIT
- AI Institute “Geometry of Deep Learning” 2019
Deep learning is transforming the field of artificial intelligence, yet it is lacking solid theoretical underpinnings. This state of affair significantly hinders further progress, as exemplified by time-consuming hyperparameters optimization, or the extraordinary difficulties encountered in adversarial machine learning. Our three-day workshop stems on what we identify as the current main bottleneck: understanding the geometrical structure of deep neural networks. This problem is at the confluence of mathematics, computer science, and practical machine learning. We invite the leaders in these fields to bolster new collaborations and to look for new angles of attack on the mysteries of deep learning.
Day 3 | 9:00 AM – 10:00 AM | Piotr Indyk, MIT
Speaker Details
Piotr Indyk is a Ph.D. student in the Department of Computer Science at Stanford University. He got his magister degree from University of Warsaw, Poland in 1995. His research has been focused on developing efficient algorithms for Computational Geometry problems in high dimensions, with applications to databases and information retrieval. His interests also include efficient algorithms for geometric and combinatorial pattern matching, approximation algorithms and machine learning.
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