soumith chintala, artificial intelligence research engineer, facebook at mlconf nyc - 4/15/16

Predicting the Future using Deep Adversarial Networks

Soumith ChintalaFacebook AI Research

Learning With No Labeled Data

Overviewof the talk

• The problem at hand • What are the benefits? • How did we solve it • What have we achieved • What’s left?

You are here

You are here

Walk here!

Route 1

Route 2

Route 3

Let’s Train a Route Generator

Route Generator

Training Data

Linear Regressor with Mean-square Error

Route Generator

RouteGenerator

Linear Regressor with Mean-square Error

Route Generator

RouteGeneratornoise

Linear Regressor with Mean-square Error

Route Generator

RouteGeneratornoise Route

Linear Regressor with Mean-square Error

Route Generator

RouteGeneratornoise Route Optimizer

Training Data

Loss: MSE

Route Generator

Training Data

Linear Regressor with Mean-square Error

Route Generator

Eh?

Linear Regressor with Mean-square Error

Route Generator

Eh?

Linear Regressor with Mean-square Error

Route Generator

Eh? Eh?

Linear Regressor with Mean-square Error

Route Generator

Eh? Eh? Eh?

Linear Regressor with Mean-square Error

Route Generator

Eh? Eh? Eh? Eh?

Linear Regressor with Mean-square Error

Route Generator

Eh? Eh? Eh? Eh? Eh?

Linear Regressor with Mean-square Error

Route Generator

Problem!Converges to the mean

of training samples

Linear Regressor with Mean-square Error

Route Generator

Which is not a valid route!

Problem!Converges to the mean

of training samples

Linear Regressor with Mean-square Error

Route Generator

Let’s try again!

Linear Regressor with Route Validator

Route Generator

RouteGenerator

noiseRoute Optimizer

Training Data

Loss: MSEpoints

Route Generator

RouteGenerator Route Optimizer

Training Data

Loss: Valid Route

Linear Regressor with Route Validator

noise

points

Route Generator

RouteGenerator Route Optimizer

Training Data

Loss: Valid Route

Linear Regressor with Route Validator

noise

points

Route Generator

RouteGenerator Route Optimizer

Training Data

Loss: Valid Route

Linear Regressor with Route Validator

????

noise

points

Generator

Generator Sample Optimizer

Training Data

Loss: Looks Real????

noise

points

Generator

Generatornoise Sample Optimizer

Training Data

Loss: Looks Real

Generator

Generatornoise SampleClassification

Loss

Training Data

Learnt Real/Fake Cost function

Discriminator

Generator

Generatornoise SampleClassification

Loss

Training Data

Neural Net

Discriminator

Neural Net

Generator

Generatornoise SampleClassification

Loss

Training Data

Discriminator

Trained via Gradient Descent

Generator

Generatornoise SampleClassification

Loss

Training Data

Discriminator

Optimizing to fool D

Generator

Generatornoise SampleClassification

Loss

Training Data

Discriminator

Optimizing to not get fooled by G

Route 4

Route Crazy!

Route Crazy! But valid.

Generator

Generatornoise

SampleClassification

Loss

Training Data

Discriminator

Optimizing to not get fooled by G

class

Generator

Generatornoise SampleClassification

Loss

Training Data

Discriminator

Optimizing to not get fooled by G

Generator

Generatornoise SampleClassification

Loss

Training Data

Discriminator

Optimizing to not get fooled by G

MSE Loss

Uses

• Unsupervised Learning • Learn when there’s little labeled data

• Planning • Look-ahead to take better decisions