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Privacy in Deep Learning: A Survey

May 09, 2020
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh


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Bit-Parallel Vector Composability for Neural Acceleration

Apr 11, 2020
Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh


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A Principled Approach to Learning Stochastic Representations for Privacy in Deep Neural Inference

Mar 26, 2020
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Ali Jalali, Ahmed Taha Elthakeb, Dean Tullsen, Hadi Esmaeilzadeh


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Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices

Mar 04, 2020
Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin, Hsin-Pai Cheng, Jilei Hou, Hadi Esmaeilzadeh

* Published as a conference paper at MLSys 2020 (Oral Presentation) 

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Gradient-Based Deep Quantization of Neural Networks through Sinusoidal Adaptive Regularization

Feb 29, 2020
Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Tarek Elgindi, Charles-Alban Deledalle, Hadi Esmaeilzadeh

* Preliminary work. Under review 

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Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation

Jan 23, 2020
Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh

* Published as a conference paper at ICLR 2020. arXiv admin note: text overlap with arXiv:1905.12799 

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Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks

Jul 24, 2019
Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh


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Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation

May 30, 2019
Byung Hoon Ahn, Prannoy Pilligundla, Hadi Esmaeilzadeh


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Shredder: Learning Noise to Protect Privacy with Partial DNN Inference on the Edge

May 26, 2019
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Prakash Ramrakhyani, Dean Tullsen, Hadi Esmaeilzadeh


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SinReQ: Generalized Sinusoidal Regularization for Automatic Low-Bitwidth Deep Quantized Training

May 04, 2019
Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh


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ReLeQ: An Automatic Reinforcement Learning Approach for Deep Quantization of Neural Networks

Dec 10, 2018
Amir Yazdanbakhsh, Ahmed T. Elthakeb, Prannoy Pilligundla, FatemehSadat Mireshghallah, Hadi Esmaeilzadeh


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ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks

Nov 05, 2018
Ahmed T. Elthakeb, Prannoy Pilligundla, Amir Yazdanbakhsh, Sean Kinzer, Hadi Esmaeilzadeh


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In-RDBMS Hardware Acceleration of Advanced Analytics

Sep 18, 2018
Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, Hadi Esmaeilzadeh

* Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, and Hadi Esmaeilzadeh. In-RDBMS Hardware Acceleration of Advanced Analytics. PVLDB, 11(11): 1317-1331, 2018 

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Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks

May 30, 2018
Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Joon Kyung Kim, Vikas Chandra, Hadi Esmaeilzadeh


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GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks

May 10, 2018
Amir Yazdanbakhsh, Hajar Falahati, Philip J. Wolfe, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh

* Proceedings of the 45th International Symposium on Computer Architecture (ISCA), 2018 

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