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Workshop on Method of Moments and Spectral Learning (ICML 2014)

Past workshops and tutorials. Workshop on Method of Moments and Spectral Learning ( ICML 2014. Location: Convention Hall No. 4E (Level 1 of the Beijing International Convention Center). Many problems in machine learning involve collecting high-dimensional multivariate observations or sequences of observations, and then fitting a compact model which explains these observations. The predominant approaches used in machine learning for fitting models are based either on the principle of maximum likelihoo...

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Workshop on Method of Moments and Spectral Learning (ICML 2014) | spectrallearning.github.io Reviews

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Past workshops and tutorials. Workshop on Method of Moments and Spectral Learning ( ICML 2014. Location: Convention Hall No. 4E (Level 1 of the Beijing International Convention Center). Many problems in machine learning involve collecting high-dimensional multivariate observations or sequences of observations, and then fitting a compact model which explains these observations. The predominant approaches used in machine learning for fitting models are based either on the principle of maximum likelihoo...

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1 main

2 call for papers

3 invited speakers

4 schedule and abstracts

5 selected bibliography

6 organization

7 important dates

8 coupons

9 reviews

10 scam

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Workshop on Method of Moments and Spectral Learning (ICML 2014) | spectrallearning.github.io Reviews

https://spectrallearning.github.io

Past workshops and tutorials. Workshop on Method of Moments and Spectral Learning ( ICML 2014. Location: Convention Hall No. 4E (Level 1 of the Beijing International Convention Center). Many problems in machine learning involve collecting high-dimensional multivariate observations or sequences of observations, and then fitting a compact model which explains these observations. The predominant approaches used in machine learning for fitting models are based either on the principle of maximum likelihoo...

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spectrallearning.github.io

1

Past workshops and tutorials

https://spectrallearning.github.io/icml2014/past.html

Past workshops and tutorials. Past workshops and tutorials. Spectral Learning Workshop (NIPS 2013). Spectral Learning Workshop (ICML 2013). Spectral Learning Workshop (NIPS 2012). Tutorial on Spectral Approaches to Learning Latent Variable Models (ICML 2012). Tutorial on Tensor Decomposition Algorithms for Latent Variable Model Estimation (ICML 2013).

2

Selected bibliography

https://spectrallearning.github.io/icml2014/bib.html

Past workshops and tutorials. D Achlioptas and F. McSherry. On spectral learning of mixtures of distributions. In COLT, 2005. A Anandkumar, K. Chaudhuri, D. Hsu, S.Kakade, L. Song and T. Zhang, Spectral Methods for Learning Multivariate Latent Tree Structure. Advances in Neural Information Processing Systems (NIPS) 25 , 2011. A Anandkumar, R. Ge, D. Hsu, S. M. Kakade, and T. Telgarsky. Tensor decompositions for learning latent variable models, 2012. arXiv:1210.7559. B Balle, A. Quattoni, and X. C...B Bal...

3

Invited speakers

https://spectrallearning.github.io/icml2014/invited.html

Past workshops and tutorials.

4

Schedule and abstracts

https://spectrallearning.github.io/icml2014/schedule.html

Past workshops and tutorials. Date: Wednesday, June 25, 2014. Location: Convention Hall No. 4E (Level 1 of the Beijing International Convention Center). Invited talk: Elina Robeva. Invited talk: Prateek Jain. Invited talk: Aravindan Vijayaraghavan. Invited talk: Anima Anandkumar. Elina Robeva (UC Berkeley):. Prateek Jain (MSR India):. Provable Non-convex Projections for Low-rank Matrix Recovery. Smoothed Analysis of Tensor Decompositions and Learning Overcomplete Latent Variable Models. Chi Wang, Xueqing...

5

Call for papers

https://spectrallearning.github.io/icml2014/cfp.html

Past workshops and tutorials. We invite submissions of papers related to method of moments / spectral methods in machine learning. We strongly support a broad definition of spectral learning as any method for learning or fitting a model based on a spectral decomposition of observable data. Extended abstracts should be submitted using the ICML 2014 format with a maximum of 4 pages (not including references). Please e-mail your submission to workshop.spectral.learning@gmail.com. Workshop: June 25, 2014.

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Workshop on Method of Moments and Spectral Learning (ICML 2014)

Past workshops and tutorials. Workshop on Method of Moments and Spectral Learning ( ICML 2014. Location: Convention Hall No. 4E (Level 1 of the Beijing International Convention Center). Many problems in machine learning involve collecting high-dimensional multivariate observations or sequences of observations, and then fitting a compact model which explains these observations. The predominant approaches used in machine learning for fitting models are based either on the principle of maximum likelihoo...

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