15 results on '"Nandan Kumar"'
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2. ReLU's Revival: On the Entropic Overload in Normalization-Free Large Language Models.
3. DeepReShape: Redesigning Neural Networks for Efficient Private Inference.
4. Characterizing and Optimizing End-to-End Systems for Private Inference.
5. Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning.
6. DeepReDuce: ReLU Reduction for Fast Private Inference.
7. Circa: Stochastic ReLUs for Private Deep Learning.
8. CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale.
9. The Ramifications of Making Deep Neural Networks Compact.
10. DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs.
11. On the Demystification of Knowledge Distillation: A Residual Network Perspective.
12. E2GC: Energy-efficient Group Convolution in Deep Neural Networks.
13. DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator.
14. ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks.
15. Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance.
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