Schedule
08:30 AM Welcome and Introduction
08:40 AM Hardware Efficiency Aware Neural Architecture Search and Compression - Song Han (Invited talk)
09:10 AM Structured matrices for efficient deep learning - Sanjiv Kumar (Invited talk)
09:40 AM DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression (Talk)
10:00 AM Poster spotlight presentations (Talk)
10:30 AM Coffee Break AM (Break)
11:00 AM Understanding the Challenges of Algorithm and Hardware Co-design for Deep Neural Networks - Vivienne Sze (Invited talk)
11:30 AM Dream Distillation: A Data-Independent Model Compression Framework (Talk)
11:50 AM The State of Sparsity in Deep Neural Networks (Talk)
12:10 PM Lunch break (Break)
12:40 PM Poster session
02:00 PM DNN Training and Inference with Hyper-Scaled Precision - Kailash Gopalakrishnan (Invited talk)
02:30 PM Mixed Precision Training & Inference - Jonathan Dekhtiar (Invited talk)
03:00 PM Coffee Break PM (Break)
03:30 PM Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions (Talk)
03:50 PM Triplet Distillation for Deep Face Recognition (Talk)
04:10 PM Single-Path NAS: Device-Aware Efficient ConvNet Design (Talk)
04:30 PM Panel discussion
05:30 PM Wrap-up and Closing