1 INTRODUCTION

2 BRIEF BACKGROUND ON DEEP NEURAL NETWORKS

3 HARDWARE APPROXIMATIONS FOR DNNS

4 ERROR COMPENSATION TECHNIQUES

5 ENERGY-ACCURACY EVALUATION

6 NOT JUST ENERGY EFFICIENCY

7 CONCLUSIONS, CHALLENGES, AND PERSPECTIVE