[AI Seminar] AI Seminar sponsored by Apple -- Brandon Amos -- Nov 28

[Adams Wei Yu]

Dear faculty and students,

We look forward to seeing you next Tuesday, Nov 28, at noon in NSH 3305 for
AI Seminar sponsored by Apple. To learn more about the seminar series,
please visit the AI Seminar webpage <http://www.cs.cmu.edu/~aiseminar/>.

On Tuesday, Brandon Amos <http://bamos.github.io/> will give the following
talk:

Title: Modern Convex Optimization within Deep Learning

Abstract:

This talk discusses a new paradigm for deep learning that integrates the
solution of optimization problems "into the loop." We highlight two
challenges present in today's deep learning landscape that involve adding
structure to the input or latent space of a model. We will discuss how to
overcome some of these challenges with the use of learnable optimization
sub-problems that subsume standard architectures and layers. These
architectures obtain state-of-the-art empirical results in many domains
such as continuous action reinforcement learning and tasks that involve
learning hard constraints like the game Sudoku.

We will cover topics from these two papers:

1. Input Convex Neural Networks. Brandon Amos, Lei Xu, J. Zico Kolter. ICML
2017. https://arxiv.org/abs/1609.07152.

2. OptNet: Differentiable Optimization as a Layer in Neural Networks.
Brandon Amos, J. Zico Kolter. ICML 2017. https://arxiv.org/abs/1703.00443.

Joint work with J. Zico Kolter.
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