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Alistair Stewart
Alistair Stewart
Web3 foundation
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Title
Cited by
Cited by
Year
Robust estimators in high-dimensions without the computational intractability
I Diakonikolas, G Kamath, D Kane, J Li, A Moitra, A Stewart
SIAM Journal on Computing 48 (2), 742-864, 2019
3672019
Sever: A robust meta-algorithm for stochastic optimization
I Diakonikolas, G Kamath, D Kane, J Li, J Steinhardt, A Stewart
International Conference on Machine Learning, 1596-1606, 2019
2182019
Being robust (in high dimensions) can be practical
I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart
International Conference on Machine Learning, 999-1008, 2017
1942017
Statistical query lower bounds for robust estimation of high-dimensional gaussians and gaussian mixtures
I Diakonikolas, DM Kane, A Stewart
2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), 73-84, 2017
1652017
List-decodable robust mean estimation and learning mixtures of spherical gaussians
I Diakonikolas, DM Kane, A Stewart
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018
1152018
Efficient algorithms and lower bounds for robust linear regression
I Diakonikolas, W Kong, A Stewart
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019
1142019
Robustly learning a gaussian: Getting optimal error, efficiently
I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018
1132018
Learning geometric concepts with nasty noise
I Diakonikolas, DM Kane, A Stewart
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018
602018
Testing bayesian networks
CL Canonne, I Diakonikolas, DM Kane, A Stewart
Conference on Learning Theory, 370-448, 2017
602017
Robust learning of fixed-structure Bayesian networks
Y Cheng, I Diakonikolas, D Kane, A Stewart
Advances in Neural Information Processing Systems 31, 2018
52*2018
Overview of polkadot and its design considerations
J Burdges, A Cevallos, P Czaban, R Habermeier, S Hosseini, F Lama, ...
arXiv preprint arXiv:2005.13456, 2020
382020
The fourier transform of poisson multinomial distributions and its algorithmic applications
I Diakonikolas, DM Kane, A Stewart
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
382016
Testing conditional independence of discrete distributions
CL Canonne, I Diakonikolas, DM Kane, A Stewart
2018 Information Theory and Applications Workshop (ITA), 1-57, 2018
362018
Optimal learning via the fourier transform for sums of independent integer random variables
I Diakonikolas, DM Kane, A Stewart
Conference on Learning Theory, 831-849, 2016
342016
Efficient robust proper learning of log-concave distributions
I Diakonikolas, DM Kane, A Stewart
arXiv preprint arXiv:1606.03077, 2016
272016
Polynomial time algorithms for multi-type branching processesand stochastic context-free grammars
K Etessami, A Stewart, M Yannakakis
Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012
272012
Learning multivariate log-concave distributions
I Diakonikolas, DM Kane, A Stewart
Conference on Learning Theory, 711-727, 2017
262017
Outlier-robust high-dimensional sparse estimation via iterative filtering
I Diakonikolas, D Kane, S Karmalkar, E Price, A Stewart
Advances in Neural Information Processing Systems 32, 2019
252019
Properly learning poisson binomial distributions in almost polynomial time
I Diakonikolas, DM Kane, A Stewart
Conference on Learning Theory, 850-878, 2016
252016
Polynomial time algorithms for branching Markov decision processes and probabilistic min (max) polynomial Bellman equations
K Etessami, A Stewart, M Yannakakis
International Colloquium on Automata, Languages, and Programming, 314-326, 2012
23*2012
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