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2020 – today
- 2024
[j8]Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak:
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression. J. Mach. Learn. Res. 25: 231:1-231:40 (2024)- [j7]Rahul Parhi
, Michael Unser:
Distributional Extension and Invertibility of the \(\boldsymbol{k}\)-Plane Transform and Its Dual. SIAM J. Math. Anal. 56(4): 4662-4686 (2024) - [i10]Rahul Parhi, Pakshal Bohra, Ayoub El Biari, Mehrsa Pourya, Michael Unser:
Random ReLU Neural Networks as Non-Gaussian Processes. CoRR abs/2405.10229 (2024) - 2023
- [j6]Rahul Parhi, Michael Unser:
The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems. IEEE Signal Process. Lett. 30: 568-572 (2023) - [j5]Rahul Parhi, Robert D. Nowak:
Deep Learning Meets Sparse Regularization: A signal processing perspective. IEEE Signal Process. Mag. 40(6): 63-74 (2023) - [j4]Rahul Parhi, Robert D. Nowak:
Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks. IEEE Trans. Inf. Theory 69(2): 1125-1140 (2023) - [i9]Rahul Parhi, Robert D. Nowak:
Deep Learning Meets Sparse Regularization: A Signal Processing Perspective. CoRR abs/2301.09554 (2023) - [i8]Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak:
Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization. CoRR abs/2305.16534 (2023) - [i7]Ronald A. DeVore, Robert D. Nowak, Rahul Parhi, Jonathan W. Siegel:
Weighted variation spaces and approximation by shallow ReLU networks. CoRR abs/2307.15772 (2023) - [i6]Rahul Parhi, Michael Unser:
Banach Space Optimality of Neural Architectures With Multivariate Nonlinearities. CoRR abs/2310.03696 (2023) - 2022
- [j3]Rahul Parhi, Robert D. Nowak:
What Kinds of Functions Do Deep Neural Networks Learn? Insights from Variational Spline Theory. SIAM J. Math. Data Sci. 4(2): 464-489 (2022) - [c3]Rahul Parhi, Robert D. Nowak:
On Continuous-Domain Inverse Problems with Sparse Superpositions of Decaying Sinusoids as Solutions. ICASSP 2022: 5603-5607 - 2021
- [j2]Rahul Parhi, Robert D. Nowak:
Banach Space Representer Theorems for Neural Networks and Ridge Splines. J. Mach. Learn. Res. 22: 43:1-43:40 (2021) - [i5]Rahul Parhi, Robert D. Nowak:
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory. CoRR abs/2105.03361 (2021) - [i4]Rahul Parhi, Robert D. Nowak:
Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks. CoRR abs/2109.08844 (2021) - 2020
- [j1]Rahul Parhi, Robert D. Nowak:
The Role of Neural Network Activation Functions. IEEE Signal Process. Lett. 27: 1779-1783 (2020) - [i3]Rahul Parhi, Robert D. Nowak:
Neural Networks, Ridge Splines, and TV Regularization in the Radon Domain. CoRR abs/2006.05626 (2020)
2010 – 2019
- 2019
- [i2]Rahul Parhi, Robert D. Nowak:
Minimum "Norm" Neural Networks are Splines. CoRR abs/1910.02333 (2019) - 2018
- [c2]Rahul Parhi, Michael Schliep, Nicholas Hopper:
MP3: A More Efficient Private Presence Protocol. Financial Cryptography 2018: 38-57 - 2016
- [i1]Rahul Parhi, Michael Schliep, Nicholas Hopper:
MP3: A More Efficient Private Presence Protocol. CoRR abs/1609.02987 (2016) - 2015
- [c1]Rahul Parhi, Chris H. Kim, Keshab K. Parhi:
Fault-tolerant ripple-carry binary adder using partial triple modular redundancy (PTMR). ISCAS 2015: 41-44
Coauthor Index
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