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A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes


Apr 20, 2022
Shaojin Ding, Weiran Wang, Ding Zhao, Tara N. Sainath, Yanzhang He, Robert David, Rami Botros, Xin Wang, Rina Panigrahy, Qiao Liang, Dongseong Hwang, Ian McGraw, Rohit Prabhavalkar, Trevor Strohman

* Submitted to INTERSPEECH 2022 

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Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture


Dec 21, 2021
Zihao Deng, Zee Fryer, Brendan Juba, Rina Panigrahy, Xin Wang


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One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks


Mar 29, 2021
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang

* 30 pages, 6 figures 

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For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions


Mar 11, 2021
Nishanth Dikkala, Gal Kaplun, Rina Panigrahy


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Learning the gravitational force law and other analytic functions


May 15, 2020
Atish Agarwala, Abhimanyu Das, Rina Panigrahy, Qiuyi Zhang


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How does the Mind store Information?


Oct 03, 2019
Rina Panigrahy


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Recursive Sketches for Modular Deep Learning


May 29, 2019
Badih Ghazi, Rina Panigrahy, Joshua R. Wang

* Published in ICML 2019 

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On the Learnability of Deep Random Networks


Apr 08, 2019
Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy


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Learning Two layer Networks with Multinomial Activation and High Thresholds


Mar 21, 2019
Surbhi Goel, Rina Panigrahy


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