학술논문

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발행년	- (예 : 2010-2015)

전체선택

Reconstructing cancer drug response networks using multitask learning

Academic Journal

Ruffalo, M.; Stojanov, P.; Pillutla, V.K.; Bar-Joseph, Z.; Varma, R.

In: BMC Systems Biology. (BMC Systems Biology, 10 October 2017, 11(1))

EBSCOHost PDF Full Text (ProQuest Central) Full Text (Gale Academic Onefile) Open Access (BioMed Central) Scopus Find it@PNU

A markov chain theory approach to characterizing the minimax optimality of stochastic gradient descent (for Least Squares)

Conference

Jain, P.; Netrapalli, P.; Kakade, S.M.; Kidambi, R.; Pillutla, V.K.; Sidford, A.

In: Leibniz International Proceedings in Informatics, LIPIcs, 37th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2017. (Leibniz International Proceedings in Informatics, LIPIcs, 1 January 2018, 93)

Scopus Find it@PNU

Data driven resource allocation for distributed learning

Conference

Dick, T.; Li, M.; White, C.; Balcan, M.F.; Pillutla, V.K.; Smola, A.

In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017. (Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 2017)

Scopus Find it@PNU

Data driven resource allocation for distributed learning

Conference

Dick, T.; White, C.; Li, M.; Balcan, M.F.; Smola, A.; Pillutla, V.K.

In: AAAI Workshop - Technical Report, Workshops of the 31st AAAI Conference on Artificial Intelligence, AAAI 2017. (AAAI Workshop - Technical Report, 2017, WS-17-01 - WS-17-15:478-484)

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On skewed multi-dimensional distributions: The FusionRP model, algorithms, and discoveries

Conference

Pillutla, V.K.; Fang, Z.; Faloutsos, C.; Tang, J.; Devineni, P.; Koutra, D.

In: 16th SIAM International Conference on Data Mining 2016, SDM 2016, 16th SIAM International Conference on Data Mining 2016, SDM 2016. (16th SIAM International Conference on Data Mining 2016, SDM 2016, 2016, :783-791)

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