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DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs., , , and . ACM J. Emerg. Technol. Comput. Syst., 17 (1): 5:1-5:25 (2020)ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks., , , , and . WACV, page 1616-1625. IEEE, (2020)Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance., and . CoRR, (2020)DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator., , , , , and . ISVLSI, page 574-579. IEEE, (2020)On the Demystification of Knowledge Distillation: A Residual Network Perspective., , and . CoRR, (2020)The Ramifications of Making Deep Neural Networks Compact., , and . VLSID, page 215-220. IEEE, (2019)E2GC: Energy-efficient Group Convolution in Deep Neural Networks., , , and . VLSID, page 155-160. IEEE, (2020)Digital Storytelling: The Integration of Intangible and Tangible Heritage in the City of Surat, India., , , , , , and . HCI (33), volume 12794 of Lecture Notes in Computer Science, page 152-168. Springer, (2021)CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale., , , , and . CoRR, (2021)Characterizing and Optimizing End-to-End Systems for Private Inference., , , , and . CoRR, (2022)