41![Fast Convergence of Stochastic Gradient Descent under a Strong Growth Condition Mark Schmidt and Nicolas Le Roux May 16, Fast Convergence of Stochastic Gradient Descent under a Strong Growth Condition Mark Schmidt and Nicolas Le Roux May 16,](https://www.pdfsearch.io/img/b2bced10c4cc9fd73f2d301d96987ca8.jpg) | Add to Reading ListSource URL: nicolas.le-roux.nameLanguage: English - Date: 2013-10-09 16:52:30
|
---|
42![Case Study 1: Estimating Click Probabilities Stochastic Gradient Descent (continued) Machine Learning/Statistics for Big Data CSE599C1/STAT592, University of Washington Case Study 1: Estimating Click Probabilities Stochastic Gradient Descent (continued) Machine Learning/Statistics for Big Data CSE599C1/STAT592, University of Washington](https://www.pdfsearch.io/img/6308f5cc7858dd6279e6fc23868442eb.jpg) | Add to Reading ListSource URL: courses.cs.washington.eduLanguage: English - Date: 2013-01-17 04:16:10
|
---|
43![WIC Wintermeeting, February 1, 2016 From Data Compression to Online Machine Learning Tim van Erven WIC Wintermeeting, February 1, 2016 From Data Compression to Online Machine Learning Tim van Erven](https://www.pdfsearch.io/img/d8f2a3f12f7ef4ab103eac7d61078d69.jpg) | Add to Reading ListSource URL: www.timvanerven.nlLanguage: English - Date: 2016-02-01 08:21:05
|
---|
44![Optimizing Non-decomposable Performance Measures: A Tale of Two Classes Harikrishna Narasimhan∗ Indian Institute of Science, Bangalore, INDIA HARIKRISHNA @ CSA . IISC . ERNET. IN Optimizing Non-decomposable Performance Measures: A Tale of Two Classes Harikrishna Narasimhan∗ Indian Institute of Science, Bangalore, INDIA HARIKRISHNA @ CSA . IISC . ERNET. IN](https://www.pdfsearch.io/img/f1d4525fd9c66137bdb1e5854dcfafbf.jpg) | Add to Reading ListSource URL: jmlr.orgLanguage: English - Date: 2015-09-16 19:38:47
|
---|
45![ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models Sanjay Krishnan, Jiannan Wang, Eugene Wu † , Michael J. Franklin, Ken Goldberg UC Berkeley, † Columbia University {sanjaykrishnan, jnwang, fran ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models Sanjay Krishnan, Jiannan Wang, Eugene Wu † , Michael J. Franklin, Ken Goldberg UC Berkeley, † Columbia University {sanjaykrishnan, jnwang, fran](https://www.pdfsearch.io/img/fbac7795860753df79695921afeffd2d.jpg) | Add to Reading ListSource URL: sampleclean.orgLanguage: English - Date: 2016-01-15 13:57:46
|
---|
46![Tracking Time-Varying Hidden Faults using Stochastic Gradient Descent Joh n C. Pla t t , Em r e K c m a n , Da vid A. Ma lt z Microsoft Research, 1 Microsoft Way, Redmond WA 98052 {jplatt, emrek, dmaltz}@microsoft.com ht Tracking Time-Varying Hidden Faults using Stochastic Gradient Descent Joh n C. Pla t t , Em r e K c m a n , Da vid A. Ma lt z Microsoft Research, 1 Microsoft Way, Redmond WA 98052 {jplatt, emrek, dmaltz}@microsoft.com ht](https://www.pdfsearch.io/img/43dc449964ef12b87988843c62f62e09.jpg) | Add to Reading ListSource URL: snowbird.djvuzone.orgLanguage: English - Date: 2007-03-09 02:31:33
|
---|
47![Stability and optimality in stochastic gradient descent arXiv:1505.02417v1 [stat.ME] 10 May 2015 Panos Toulis, Dustin Tran, and Edoardo M. Airoldi Harvard University Stability and optimality in stochastic gradient descent arXiv:1505.02417v1 [stat.ME] 10 May 2015 Panos Toulis, Dustin Tran, and Edoardo M. Airoldi Harvard University](https://www.pdfsearch.io/img/7d72d00e2ed2230b8187a13f3e067214.jpg) | Add to Reading ListSource URL: arxiv.orgLanguage: English - Date: 2015-05-11 20:26:25
|
---|
48![Stochastic Gradient Descent with Importance Sampling Rachel Ward UT Austin Joint work with Deanna Needell (Claremont McKenna College) Stochastic Gradient Descent with Importance Sampling Rachel Ward UT Austin Joint work with Deanna Needell (Claremont McKenna College)](https://www.pdfsearch.io/img/9979bc2057b741a6270ea60dd76e4335.jpg) | Add to Reading ListSource URL: www.ma.utexas.eduLanguage: English - Date: 2014-08-12 15:41:58
|
---|
49![Gossip Learning with Linear Models on Fully Distributed Data∗ Róbert Ormándi, István Heged˝us, Márk Jelasity University of Szeged and Hungarian Academy of Sciences {ormandi,ihegedus,jelasity}@inf.u-szeged.hu Gossip Learning with Linear Models on Fully Distributed Data∗ Róbert Ormándi, István Heged˝us, Márk Jelasity University of Szeged and Hungarian Academy of Sciences {ormandi,ihegedus,jelasity}@inf.u-szeged.hu](https://www.pdfsearch.io/img/663dbda100ae8b038f950d21e5febcc8.jpg) | Add to Reading ListSource URL: www.inf.u-szeged.huLanguage: English - Date: 2013-02-15 04:43:56
|
---|
50![Sparse Online Learning via Truncated Gradient John Langford Yahoo! Research Sparse Online Learning via Truncated Gradient John Langford Yahoo! Research](https://www.pdfsearch.io/img/b9baa365029b8c6f0bc6d5ef80e97949.jpg) | Add to Reading ListSource URL: hunch.netLanguage: English - Date: 2009-01-11 09:13:59
|
---|