закладки (спрятать)627
- Theory of Deep Learning Conference
- Math, Theoretical CS, Stats and Optimization courses
- Optimization and Machine Learning Seminar
- High Dimensional Statistics by Arora
- Math Video Lectures
- Book for Machine Learning by Hal Daume
- PfHP Lots of loops to parallelize
- Recent & Upcoming Talks | Harvard ML Theory
- Advice on writing research papers
публикации (спрятать)2111
- (2020)cite arxiv:2009.06736Comment: 17 pages. To appear, Bulletin of the American Mathematical Society.
- (2020)cite arxiv:2009.08092Comment: PN, YB co-first authors.
- (2020)cite arxiv:2007.06140Comment: 21 pages, 12 figures, 4 tables.
- (2011)
- (2014)
- (2020)
- (2019)
- стр. 3179-3189. (2018)
- (2017)cite arxiv:1708.00002Comment: To appear in SODA 2018.
- (2019)
- (2020)cite arxiv:2007.01160Comment: 25 pages.
- (2020)cite arxiv:2008.00601Comment: 58 pages (not including title page).
- (2020)cite arxiv:2008.01036.
- (2020)cite arxiv:2006.14548Comment: 11 pages of main text. 60 pages total.
- (2016)cite arxiv:1607.00550.
- (2020)
- IEEE Access, (2020)
- (2020)cite arxiv:2006.09065.
- (2020)cite arxiv:2006.08063.
- (2019)cite arxiv:1909.03172Comment: International Conference on Machine Learning (ICML), 2019.
- (2020)cite arxiv:2002.11328.
- (2020)cite arxiv:2006.12301Comment: Correct some typos; 46 Pages, 41 figures.
- Proceedings of the 36th International Conference on Machine Learning, том 97 из Proceedings of Machine Learning Research, стр. 862--871. Long Beach, California, USA, PMLR, (09--15 Jun 2019)
- (2020)cite arxiv:2005.13239Comment: First two authors contributed equally. Last two authors advised equally.
- (2020)cite arxiv:2007.00151.
- (2020)cite arxiv:2007.04528.
- (2020)cite arxiv:2007.04470Comment: 16 pages, 1 figure.
- (2020)cite arxiv:2007.04532.
- (2020)cite arxiv:2007.04466Comment: Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning.
- (2020)
- (2020)cite arxiv:2003.06121Comment: under review for ICML 2020.
- (2020)cite arxiv:2005.08099Comment: 175 pages; subsumes preliminary draft arXiv:1908.06130; accepted for presentation at the Conference on Learning Theory (COLT) 2020.
- (2020)cite arxiv:2007.04458.
- (2017)cite arxiv:1711.03707.
- (2018)cite arxiv:1810.12272Comment: Full version of a work with the same title that will appear in NIPS 2018, 31 pages containing 5 figures, 1 table, 2 algorithms.
- (2018)cite arxiv:1809.03063.
- (2019)cite arxiv:1905.12202Comment: 17 pages, 3 figures, 5 tables; NeurIPS final version.
- (2019)cite arxiv:1907.05401.
- стр. 4712-4722. (2019)
- Proceedings of the 35th International Conference on Machine Learning, том 80 из Proceedings of Machine Learning Research, стр. 2019--2028. Stockholmsmässan, Stockholm Sweden, PMLR, (10--15 Jul 2018)
- (2020)cite arxiv:2007.04202Comment: ICML 2020 - Proceedings of the 37th International Conference on Machine Learning.
- (2015)
- (2020)cite arxiv:2006.15136Comment: 80 pages LaTeX.
- (2020)cite arxiv:2006.08680.
- (2020)cite arxiv:2004.12493Comment: 44 pages, 16 figures.
- (2020)cite arxiv:2006.09313Comment: 34 Pages.
- (2020)cite arxiv:2006.03627.
- (2020)cite arxiv:2006.09289.
- (2020)cite arxiv:2006.07279.
- (2020)cite arxiv:2006.09252.
- (2020)cite arxiv:2006.09989.
- Advances in Applied Mathematics, (2020)
- (2020)
- Journal of Machine Learning Research, 2 (Mar): 499-526 (2002)
- (2020)cite arxiv:2002.03432.
- (2020)cite arxiv:2006.02855Comment: 27 pages.
- (2020)cite arxiv:2006.06663.
- (1997)
- Neuron, 106 (2): 212 - 217 (2020)
- International Conference on Learning Representations, (2019)
- (2020)cite arxiv:2001.06814Comment: AISTATS2020.
- (2011)
- IEEE Transactions on Neural Networks, 6 (4): 911-917 (июля 1995)
- (2016)
- (2016)
- (2005)
- (2017)
- (2016)
- (2020)cite arxiv:2005.01643.
- (2020)cite arxiv:2006.04621Comment: submitted to Neurips 2020.
- (2020)cite arxiv:2006.04240Comment: 8 pages + detailed supplement with additional qualitative and quantitative results.
- (1947)
- (2020)cite arxiv:2006.02734Comment: 8 pages, 3 figures.
- (2020)cite arxiv:2006.02683Comment: 12 pages.
- (2020)cite arxiv:2006.02636.
- (2020)cite arxiv:2006.02624.
- (2020)cite arxiv:2006.02544Comment: 10 pages, 3 figures; 13 supplementary pages, 4 supplementary figures, 4 supplementary tables.
- (2020)cite arxiv:2006.02554Comment: 39 pages.
- (2020)cite arxiv:2006.02575Comment: ICML 2020.
- (2020)cite arxiv:2006.02516.
- (2020)cite arxiv:2006.02608.
- (2020)cite arxiv:2006.02425.
- (2020)cite arxiv:2006.01868.
- (2019)cite arxiv:1907.12998.
- International Conference on Learning Representations, (2020)
- (2019)cite arxiv:1901.02474Comment: Code is available on: https://github.com/AlexiaJM/relativistic-f-divergences.
- (2019)cite arxiv:1908.04847.
- (2019)cite arxiv:1910.11758Comment: updated paper, experiments, and writing.
- (2020)cite arxiv:2001.00610.
- Stochastic Systems, 9 (2): 83--100 (июня 2019)
- (2010)
- (2019)cite arxiv:1910.09066Comment: 26 pages; 2 figures.
- (2020)cite arxiv:2005.10242Comment: International Conference on Machine Learning (ICML), 2020.
- International Conference on Learning Representations, (2020)
- International Conference on Learning Representations, (2020)
- International Conference on Learning Representations, (2020)
- ICLR, (2020)
- International Conference on Learning Representations, (2020)
- (2020)cite arxiv:2004.00010Comment: New version: better implementation, analysis, and discussion.
- (2020)cite arxiv:2005.11084Comment: SIGGRAPH 2020; Project page: https://ranahanocka.github.io/point2mesh/.
