Publications

(2021). CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale. In Arxiv Preprint.

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(2021). Circa: Stochastic ReLUs for Private Deep Learning. In NeurIPS 2021.

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(2021). DeepReDuce: ReLU Reduction for Fast Private Inference. In ICML 2021.

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(2020). DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs. In ACM JETC 2020.

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(2020). Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance. In IEEE TC 2020.

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(2020). DRACO: Co-optimizing hardware utilization, and performance of dnns on systolic accelerator. In ISVLSI 2020.

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(2020). ULSAM: Ultra-lightweight subspace attention module for compact convolutional neural networks. In WACV 2020.

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(2020). E2GC: Energy-efficient group convolution in deep neural networks. In VLSID 2020.

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(2019). Data-type Aware Arithmetic Intensity for Deep Neural Networks. In ICCD 2019 (Poster).

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(2019). The Ramifications of Making Deep Neural Networks Compact. In VLSID 2019.

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