Abstract is missing.
- Education Abstract: Design Space Exploration for Deep Learning at the EdgeAndy D. Pimentel. 1-2 [doi]
- Enabling Energy-efficient AI Computing: Leveraging Application-specific Approximations : (Education Class)Salim Ullah, Siva Satyendra Sahoo, Akash Kumar 0001. 3-4 [doi]
- Special Session: Detecting and Defending Vulnerabilities in Heterogeneous and Monolithic Systems: Current Strategies and Future DirectionsVenkat Nitin Patnala, Sai Manoj Pudukotai Dinakarrao, Guru Venkataramani, Jie Chen 0020, Preet Derasari, Milos Doroslovacki, Fan Yao, Hongyu Fang, Meron Demissie, Todd M. Austin, Lauren Biernacki, Saket Upadhyay, Arnabjyoti Kalita, Ashish Venkat. 5-14 [doi]
- What do Transformers have to learn from Biological Spiking Neural Networks?Jason K. Eshraghian, Rui-Jie Zhu. 15-16 [doi]
- Efficient Neural Networks: from SW optimization to specialized HW acceleratorsMarcello Traiola, Angeliki Kritikakou, Silviu-Ioan Filip, Olivier Sentieys. 17-18 [doi]
- Primer on Data in Quantum Machine LearningAviral Shrivastava, Vinayak Sharma. 19-20 [doi]
- Work-in-Progress:ACPO: An AI-Enabled Compiler FrameworkAmir H. Ashouri, Muhammad Asif Manzoor, Minh Vu, Raymond Zhang, Ziwen Wang, Angel Zhang, Bryan Chan, Tomasz S. Czajkowski, Yaoqing Gao. 21 [doi]
- Work-in-Progress: Temporal RegionDrop - Frame Difference Sparsity for Efficient Video InferenceYouki Sada, Seiya Shibata, Yuki Kobayashi, Takashi Takenaka. 22 [doi]