1![Multiclass Boosting with Hinge Loss based on Output Coding Tianshi Gao Electrical Engineering Department, Stanford, CAUSA Daphne Koller Computer Science Department, Stanford, CAUSA Multiclass Boosting with Hinge Loss based on Output Coding Tianshi Gao Electrical Engineering Department, Stanford, CAUSA Daphne Koller Computer Science Department, Stanford, CAUSA](https://www.pdfsearch.io/img/17415031016e558c0d675282df58fe10.jpg) | Add to Reading ListSource URL: robotics.stanford.eduLanguage: English - Date: 2012-08-02 01:49:01
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2![Robust Truncated Hinge Loss Support Vector Machines Yichao W U and Yufeng L IU The support vector machine (SVM) has been widely applied for classification problems in both machine learning and statistics. Despite its pop Robust Truncated Hinge Loss Support Vector Machines Yichao W U and Yufeng L IU The support vector machine (SVM) has been widely applied for classification problems in both machine learning and statistics. Despite its pop](https://www.pdfsearch.io/img/99ee7e3590e9227a8a355e9c7663ba38.jpg) | Add to Reading ListSource URL: www.unc.eduLanguage: English - Date: 2007-09-14 17:32:27
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3![Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs: Appendices A. Probabilistic Soft Logic users (i.e., users that are not top users). Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs: Appendices A. Probabilistic Soft Logic users (i.e., users that are not top users).](https://www.pdfsearch.io/img/1b0e323256f9995c8261f70b6ed2fc23.jpg) | Add to Reading ListSource URL: psl.umiacs.umd.edu- Date: 2015-05-18 20:16:52
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4![In this talk, I will introduce hinge-loss Markov random fields (HLMRFs), a new kind of probabilistic graphical model that supports scalable collective inference from richly structured data. HL-MRFs unify three different In this talk, I will introduce hinge-loss Markov random fields (HLMRFs), a new kind of probabilistic graphical model that supports scalable collective inference from richly structured data. HL-MRFs unify three different](https://www.pdfsearch.io/img/2de6938798ce32ed3af0a1cfa638e804.jpg) | Add to Reading ListSource URL: mmds-data.org- Date: 2016-06-23 15:50:48
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5![In this talk, I will introduce hinge-loss Markov random fields (HLMRFs), a new kind of probabilistic graphical model that supports scalable collective inference from richly structured data. HL-MRFs unify three different In this talk, I will introduce hinge-loss Markov random fields (HLMRFs), a new kind of probabilistic graphical model that supports scalable collective inference from richly structured data. HL-MRFs unify three different](https://www.pdfsearch.io/img/42d2cb7cf0cb829d5666a19f601b42ac.jpg) | Add to Reading ListSource URL: mmds-data.org- Date: 2016-06-23 15:50:48
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6![Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen H. Bach∗ Bert Huang∗ Jordan Boyd-Graber Lise Getoor Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen H. Bach∗ Bert Huang∗ Jordan Boyd-Graber Lise Getoor](https://www.pdfsearch.io/img/c2343ae8e1a892652417a9387b12c03e.jpg) | Add to Reading ListSource URL: stephenbach.net- Date: 2015-07-02 16:31:46
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7![Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen H. Bach∗ Bert Huang∗ Jordan Boyd-Graber Lise Getoor Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen H. Bach∗ Bert Huang∗ Jordan Boyd-Graber Lise Getoor](https://www.pdfsearch.io/img/cc5be51819a54d2d3c82b775151b7193.jpg) | Add to Reading ListSource URL: psl.umiacs.umd.edu- Date: 2015-07-02 16:23:02
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8![http://linqs.cs.umd.edu I Learning Latent Groups with Hinge-loss Markov Random Fields http://linqs.cs.umd.edu I Learning Latent Groups with Hinge-loss Markov Random Fields](https://www.pdfsearch.io/img/f60ca15cb7578049002931cce1868fec.jpg) | Add to Reading ListSource URL: stephenbach.net- Date: 2013-06-12 13:48:37
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9![Collective Activity Detection using Hinge-loss Markov Random Fields Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry Davis University of Maryland College Park, MD 20742 {blondon,sameh,bach,bert,g Collective Activity Detection using Hinge-loss Markov Random Fields Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry Davis University of Maryland College Park, MD 20742 {blondon,sameh,bach,bert,g](https://www.pdfsearch.io/img/a7243162358c683b0a672fd165fe236c.jpg) | Add to Reading ListSource URL: psl.umiacs.umd.eduLanguage: English - Date: 2013-06-14 19:26:52
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10![Hinge-Loss Markov Random Fields and Probabilistic Soft Logic arXiv:1505.04406v2 [cs.LG] 9 DecStephen H. Bach∗ Matthias Broecheler† Bert Huang‡ Lise Getoor§ Hinge-Loss Markov Random Fields and Probabilistic Soft Logic arXiv:1505.04406v2 [cs.LG] 9 DecStephen H. Bach∗ Matthias Broecheler† Bert Huang‡ Lise Getoor§](https://www.pdfsearch.io/img/86a7d5b43628b35c91d9a601efbee40a.jpg) | Add to Reading ListSource URL: stephenbach.netLanguage: English - Date: 2015-12-16 16:04:19
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