Digvijay Boob
Title
Cited by
Cited by
Year
Theoretical properties of the global optimizer of two layer neural network
D Boob, G Lan
arXiv preprint arXiv:1710.11241, 2017
272017
Complexity of training relu neural network
D Boob, SS Dey, G Lan
arXiv preprint arXiv:1809.10787, 2018
112018
Stochastic first-order methods for convex and nonconvex functional constrained optimization
D Boob, Q Deng, G Lan
arXiv preprint arXiv:1908.02734, 2019
92019
Differentially Private Mixed-Type Data Generation For Unsupervised Learning
U Tantipongpipat, C Waites, D Boob, AA Siva, R Cummings
arXiv preprint arXiv:1912.03250, 2019
42019
Proximal point methods for optimization with nonconvex functional constraints
D Boob, Q Deng, G Lan
arXiv preprint arXiv:1908.02734, 2019
42019
Faster width-dependent algorithm for mixed packing and covering LPs
D Boob, S Sawlani, D Wang
Advances in Neural Information Processing Systems, 15279-15288, 2019
22019
Flowless: Extracting Densest Subgraphs Without Flow Computations
D Boob, Y Gao, R Peng, S Sawlani, C Tsourakakis, D Wang, J Wang
Proceedings of The Web Conference 2020, 573-583, 2020
12020
Convex and Structured Nonconvex Optimization for Modern Machine Learning: Complexity and Algorithms
DP Boob
Georgia Institute of Technology, 2020
2020
Private Synthetic Data Generation via GANs (Supporting PDF)
D Boob, R Cummings, D Kimpara, UT Tantipongpipat, C Waites, ...
2018
Differentially Private Synthetic Data Generation via GANs
D Boob, R Cummings, D Kimpara, UT Tantipongpipat, C Waites, ...
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