Yoshua Bengio – Robohub https://robohub.org Connecting the robotics community to the world Sun, 04 Oct 2026 22:52:50 +0000 en-US hourly 1 https://wordpress.org/?v=7.1.4 Future of machine learning, w. Geoffrey Hinton, Yoshua Bengio, Yann LeCun (Part 2) https://robohub.org/future-of-machine-learning-w-geoffrey-hinton-yoshua-bengio-yann-lecun-part-2/ Tue, 17 Mar 2015 14:48:51 +0000 http://robohub.org/future-of-machine-learning-w-geoffrey-hinton-yoshua-bengio-yann-lecun-part-2/ We hear the second part of our conversation with with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU). They talk with us about this history (and future) of research on neural nets. We explore how to use Determinantal Point Processes. Alex Kulesza  and Ben Taskar (who passed away recently) have done some really exciting work in this area, for more on DPPs check out their paper on the topic. 
Also, we take a listener question about machine learning and function approximation (spoiler alert: it is, and then again, it isn’t).

]]> We hear the second part of our conversation with with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU), who talk with us about the history (and future) of research on neural nets. 

We explore how to use Determinantal Point Processes. Alex Kulesza  and Ben Taskar (who passed away recently) have done some really exciting work in this area, for more on DPPs check out their paper on the topic.

Also, we take a listener question about machine learning and function approximation (spoiler alert: it is, and then again, it isn’t).

If you liked this article, you may also be interested in:

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

]]> Talking Machines: History of machine learning, w. Geoffrey Hinton, Yoshua Bengio, Yann LeCun https://robohub.org/talking-machines-history-of-machine-learning-w-geoffrey-hinton-yoshua-bengio-yann-lecun/ Thu, 26 Feb 2015 20:40:21 +0000 http://robohub.org/talking-machines-history-of-machine-learning-w-geoffrey-hinton-yoshua-bengio-yann-lecun/ In episode five of Talking Machines, we hear the first part of our conversation with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU). Ryan introduces us to the ideas in tensor factorization methods for learning latent variable models (which is both a tongue twister and and one of the new tools in ML). To find out more on the topic take a look at the work of Daniel Hsu, Animashree Anandkumar and Sham M. Kakade Plus we take a listener question about just where statistics stops and machine learning begins.

 

]]> mind-AI-intelligence-learning-data-brainIn episode five of Talking Machines, we hear the first part of our conversation with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU). Ryan introduces us to the ideas in tensor factorization methods for learning latent variable models (which is both a tongue twister and and one of the new tools in ML). To find out more on the topic take a look at the work of Daniel Hsu, Animashree Anandkumar and Sham M. Kakade Plus we take a listener question about just where statistics stops and machine learning begins.

Robohub is an online platform that brings together leading communicators in robotics research, start-ups, business, and education from around the world. Learn more about us here. If you liked this article, you may also be interested in:

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

]]> Talking Machines: Common sense problems & learning about machine learning with Kevin Murphy https://robohub.org/talking-machines-common-sense-problems-learning-about-machine-learning-with-kevin-murphy/ Thu, 29 Jan 2015 21:07:11 +0000 http://robohub.org/talking-machines-common-sense-problems-learning-about-machine-learning-with-kevin-murphy/ On episode three of Talking Machines we sit down with Kevin Murphy who is currently a research scientist at Google. We talk with him about the work he’s doing there on the Knowledge Vault, his textbook, Machine Learning: A Probabilistic Perspective (and its arch nemesis which we won’t link to), and how to learn about machine learning (Metacademy is a great place to start). 

We tackle a listener question about the dream of a one step solution to strong Artificial Intelligence and if Deep Neural Networks might be it.

Plus, Ryan introduces us to a new way of thinking about questions in machine learning from Yoshua Bengio’s Lab at the University of Montreal out lined in their new paper, Identifying and attacking the saddle point problem in high-dimensional non-convex optimization, and Katherine brings up Facebook’s release of open source machine learning tools and we talk about what it might mean. 

If you want to explore some open source tools for machine learning we also recommend giving these a try:

]]> Machine_Learning_Probabilistic_Perspective_Kevin_MurphyOn episode three of Talking Machines we sit down with Kevin Murphy, who is currently a research scientist at Google. We talk with him about the work he’s doing there on the Knowledge Vault, his textbook, Machine Learning: A Probabilistic Perspective (and its arch nemesis, which we won’t link to), and how to learn about machine learning (Metacademy is a great place to start).

We tackle a listener question about the dream of a one-step solution to strong Artificial Intelligence and if Deep Neural Networks might be it.

Plus, Ryan introduces us to a new way of thinking about questions in machine learning from Yoshua Bengio’s Lab at the University of Montreal, as outlined in their new paper, Identifying and attacking the saddle point problem in high-dimensional non-convex optimization, and Katherine brings up Facebook’s release of open source machine learning tools and we talk about what it might mean.

If you want to explore some open source tools for machine learning we also recommend giving these a try:

]]> Introducing Talking Machines: Your window into the world of machine learning https://robohub.org/introducing-talking-machines-your-window-into-the-world-of-machine-learning/ Thu, 01 Jan 2015 18:09:14 +0000 http://robohub.org/introducing-talking-machines-your-window-into-the-world-of-machine-learning/ AI_evolution_dataRobohub is excited to bring you our newest series – the Talking Machines podcast. Hosted by Katherine Gorman and Ryan Adams, Talking Machines is your window into the world of machine learning. You can catch new episodes every two weeks on Thursdays.

In the first episode of Talking Machines we meet our hosts, Katherine Gorman (nerd, journalist) and Ryan Adams (nerd, Harvard computer science professor), and explore some of the interviews you’ll be able to hear this season. Today we hear some short clips on big issues, we’ll get technical, but today is all about introductions.

We start with Kevin Murphy of Google talking about his textbook that has become a standard in the field. Then we turn to Hanna Wallach of Microsoft Research NYC and UMass Amherst and hear about the founding of WiML (Women in Machine Learning). Next we discuss academia’s relationship with business with Max Welling from the University of Amsterdam, program co-chair of  the 2013 NIPS conference (Neural Information Processing Systems). Finally, we sit down with three pillars of the field Yann LeCun, Yoshua Bengio, and Geoff Hinton to hear about where the field has been and where it might be headed.

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