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Tal Wagner
Tal Wagner
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Title
Cited by
Cited by
Year
Scalable fair clustering
A Backurs, P Indyk, K Onak, B Schieber, A Vakilian, T Wagner
International Conference on Machine Learning, 405-413, 2019
2302019
Learning space partitions for nearest neighbor search
Y Dong, P Indyk, I Razenshteyn, T Wagner
arXiv preprint arXiv:1901.08544, 2019
106*2019
Space and time efficient kernel density estimation in high dimensions
A Backurs, P Indyk, T Wagner
Advances in neural information processing systems 32, 2019
682019
Unveiling transformers with lego: a synthetic reasoning task
Y Zhang, A Backurs, S Bubeck, R Eldan, S Gunasekar, T Wagner
arXiv preprint arXiv:2206.04301, 2022
67*2022
Scalable nearest neighbor search for optimal transport
A Backurs, Y Dong, P Indyk, I Razenshteyn, T Wagner
International Conference on machine learning, 497-506, 2020
632020
Semi-supervised learning on data streams via temporal label propagation
T Wagner, S Guha, S Kasiviswanathan, N Mishra
International Conference on Machine Learning, 5095-5104, 2018
602018
Sample-optimal low-rank approximation of distance matrices
P Indyk, A Vakilian, T Wagner, DP Woodruff
Conference on Learning Theory, 1723-1751, 2019
302019
Learning-based support estimation in sublinear time
T Eden, P Indyk, S Narayanan, R Rubinfeld, S Silwal, T Wagner
arXiv preprint arXiv:2106.08396, 2021
272021
Triangle and four cycle counting with predictions in graph streams
JY Chen, T Eden, P Indyk, H Lin, S Narayanan, R Rubinfeld, S Silwal, ...
arXiv preprint arXiv:2203.09572, 2022
202022
Exponentially improving the complexity of simulating the Weisfeiler-Lehman test with graph neural networks
A Aamand, J Chen, P Indyk, S Narayanan, R Rubinfeld, N Schiefer, ...
Advances in Neural Information Processing Systems 35, 27333-27346, 2022
172022
Approximate nearest neighbors in limited space
P Indyk, T Wagner
Conference On Learning Theory, 2012-2036, 2018
162018
A graph-theoretic approach to multitasking
N Alon, D Reichman, I Shinkar, T Wagner, S Musslick, JD Cohen, ...
Advances in neural information processing systems 30, 2017
162017
Near-optimal (euclidean) metric compression
P Indyk, T Wagner
Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017
162017
Generalization bounds for data-driven numerical linear algebra
P Bartlett, P Indyk, T Wagner
Conference on Learning Theory, 2013-2040, 2022
142022
Practical data-dependent metric compression with provable guarantees
P Indyk, I Razenshteyn, T Wagner
Advances in Neural Information Processing Systems 30, 2017
142017
Towards Resistance Sparsifiers
M Dinitz, R Krauthgamer, T Wagner
arXiv preprint arXiv:1506.07568, 2015
132015
Faster kernel matrix algebra via density estimation
A Backurs, P Indyk, C Musco, T Wagner
International Conference on Machine Learning, 500-510, 2021
102021
Few-shot data-driven algorithms for low rank approximation
P Indyk, T Wagner, D Woodruff
Advances in Neural Information Processing Systems 34, 10678-10690, 2021
92021
Optimal (Euclidean) metric compression
P Indyk, T Wagner
SIAM Journal on Computing 51 (3), 467-491, 2022
62022
Multitasking capacity: Hardness results and improved constructions
N Alon, JD Cohen, TL Griffiths, P Manurangsi, D Reichman, I Shinkar, ...
SIAM Journal on Discrete Mathematics 34 (1), 885-903, 2020
62020
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