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Deep Learning Final Project

Alexander Powers

An Exploration of Multi-Task Learning

This project explores different network architectures that leverage weight sharing to improve performance on multiple tasks.

The Problem (CIFAR100)

The CIFAR100 dataset consists of RGB images, fine labels(100 classes), and coarse labels(20 classes). Each fine label class is a proper subset of a coarse label class (i.e. one fine label can't have two coarse labels and vice versa).

Architectures to be trained

1) Independent networks (the control architecture)

input_image --> conv_layers --> fc_layers --> fine_label       
input_image --> conv_layers --> fc_layers --> coarse_label

2) Hard parameter sharing in convolutional layers

                           /--> fc_layers --> fine_label
input_image --> conv_layers      
                           \--> fc_layers --> coarse_label

3) Using coarse label output as weights

input_image   ---->   conv_layers   ---->   fc_layers_1
                                                      \                
                                                    concat -> fc_layers_2  -> fine_label
                                                      /
input_image -> conv_layers -> fc_layers -> coarse_label

4) Using fine label output as weights

input_image   ---->   conv_layers   ---->   fc_layers_1
                                                      \                
                                                    concat -> fc_layers_2  -> coarse_label
                                                      /
input_image -> conv_layers -> fc_layers -> fine_label

5) Combination of 2 & 3

                         / -------------> fc_layers_1
                        /                           \
input_image -> conv_layers                        concat -> fc_layers_2 -> fine_label
                        \                           /
                         \-> fc_layers -> coarse_label

6) Combination of 2 & 4

                         / -------------> fc_layers_1
                        /                           \
input_image -> conv_layers                        concat -> fc_layers_2 -> coarse_label
                        \                           /
                         \-> fc_layers -> fine_label