Di Wang
Di Wang
Google Research
Verified email at eecs.berkeley.edu - Homepage
Cited by
Cited by
Local flow partitioning for faster edge connectivity
M Henzinger, S Rao, D Wang
SIAM Journal on Computing 49 (1), 1-36, 2020
Expander decomposition and pruning: Faster, stronger, and simpler
T Saranurak, D Wang
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019
On the security of trustee-based social authentications
NZ Gong, D Wang
IEEE transactions on information forensics and security 9 (8), 1251-1263, 2014
Bipartite matching in nearly-linear time on moderately dense graphs
J van den Brand, YT Lee, D Nanongkai, R Peng, T Saranurak, A Sidford, ...
2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020
Unified acceleration method for packing and covering problems via diameter reduction
D Wang, S Rao, MW Mahoney
arXiv preprint arXiv:1508.02439, 2015
Capacity releasing diffusion for speed and locality
D Wang, K Fountoulakis, M Henzinger, MW Mahoney, S Rao
International Conference on Machine Learning, 3598-3607, 2017
Analyzing quadratic unconstrained binary optimization problems via multicommodity flows
D Wang, R Kleinberg
Discrete Applied Mathematics 157 (18), 3746-3753, 2009
Approximating the Solution to Mixed Packing and Covering LPs in Parallel O˜(epsilon^{-3}) Time
MW Mahoney, S Rao, D Wang, P Zhang
43rd International Colloquium on Automata, Languages, and Programming (ICALP …, 2016
Minimum cost flows, MDPs, and ℓ1-regression in nearly linear time for dense instances
J van den Brand, YT Lee, YP Liu, T Saranurak, A Sidford, Z Song, D Wang
Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021
Flows in Almost Linear Time via Adaptive Preconditioning
R Kyng, R Peng, S Sachdeva, D Wang
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019
Faster parallel solver for positive linear programs via dynamically-bucketed selective coordinate descent
D Wang, M Mahoney, N Mohan, S Rao
arXiv preprint arXiv:1511.06468, 2015
Packing LPs are Hard to Solve Accurately, Assuming Linear Equations are Hard.
R Kyng, D Wang, P Zhang
ACM-SIAM Symposium on Discrete Algorithms, 2020
Targeted pandemic containment through identifying local contact network bottlenecks
S Yang, P Senapati, D Wang, CT Bauch, K Fountoulakis
PLOS Computational Biology 17 (8), e1009351, 2021
p-Norm Flow Diffusion for Local Graph Clustering
K Fountoulakis, D Wang, S Yang
International Conference on Machine Learning, 3222-3232, 2020
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
Minimum Cost Flows, MDPs, and -Regression in Nearly Linear Time for Dense Instances
J Brand, YT Lee, YP Liu, T Saranurak, A Sidford, Z Song, D Wang
arXiv preprint arXiv:2101.05719, 2021
Faster width-dependent algorithm for mixed packing and covering LPs
D Boob, S Sawlani, D Wang
Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019
Fast Approximation Algorithms for Positive Linear Programs
D Wang
University of California, Berkeley, 2017
-norm Flow Diffusion in Near-Linear Time
L Chen, R Peng, D Wang
arXiv preprint arXiv:2105.14629, 2021
Learning Robust Algorithms for Online Allocation Problems Using Adversarial Training
G Zuzic, D Wang, A Mehta, D Sivakumar
arXiv preprint arXiv:2010.08418, 2020
The system can't perform the operation now. Try again later.
Articles 1–20