Лебедев Вадим Владимирович Алгоритмы ускорения сверточных нейронных сетей / Algorithms For Speeding Up Convolutional Neural Networks

Короткий опис

Лебедев Вадим Владимирович Алгоритмы ускорения сверточных нейронных сетей / Algorithms For Speeding Up Convolutional Neural Networks
ОГЛАВЛЕНИЕ ДИССЕРТАЦИИ
кандидат наук Лебедев Вадим Владимирович
Contents

Abstract i

1 Introduction

1.1 Motivation

1.2 Problems and datasets

1.3 CNN building blocks

1.4 CNN architectures

1.5 Contribution

2 Related work

2.1 Tensor decompositions

2.2 Fast Architecture Design

2.3 Automatic architecture search

2.4 Quantization

2.5 Pruning

2.6 Teacher-student approaches

2.7 Adaptive methods

2.8 Problem-specific approaches

2.9 Summary

3 CP-decomposition of convolutional weights

3.1 Method

3.1.1 Related works

3.1.2 CP-decomposition

3.1.3 Convolutional weights approximation

3.1.4 Implementation and Fine-tuning

3.1.5 Complexity analysis

3.2 Experiments

3.2.1 Character-classification CNN

3.2.2 AlexNet

3.2.3 NLS vs. Greedy

3.3 Conclusion

4 Group-wise Brain Damage

4.1 Method

4.1.1 Group-Sparse Convolutions

4.1.2 Fixed sparsity pattern

4.1.3 Sparsifying with Group-wise Brain Damage

4.2 Experiments

4.2.1 MNIST experiments

4.2.2 ILSVRC experiments

4.3 Conclusion

5 Impostor Nets

5.1 Method

5.1.1 Motivation

5.1.2 Training impostor networks

5.2 Experiments

5.2.1 Timings

5.2.2 Open set recognition

5.2.3 Intuition behind the "loose" impostors

5.3 Conclusion

6 Conclusion and Discussion

Bibliography