Multiclass Boosting with Hinge Loss based on Output Coding Tianshi Gao Electrical Engineering Department, Stanford, CAUSA Daphne Koller Computer Science Department, Stanford, CAUSA

Source URL: robotics.stanford.edu

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

Source URL: www.unc.edu

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).

Source URL: psl.umiacs.umd.edu

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

Source URL: mmds-data.org

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

Source URL: mmds-data.org

Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen H. Bach∗ Bert Huang∗ Jordan Boyd-Graber Lise Getoor

Source URL: stephenbach.net

Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen H. Bach∗ Bert Huang∗ Jordan Boyd-Graber Lise Getoor

Source URL: psl.umiacs.umd.edu

http://linqs.cs.umd.edu I Learning Latent Groups with Hinge-loss Markov Random Fields

Source URL: stephenbach.net

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

Source URL: psl.umiacs.umd.edu

• Artificial intelligence
• Probability
• Statistics
• Bayesian statistics
• Markov networks
• Graphical models
• Markov random field
• Probability theory
• Image segmentation
• Probabilistic soft logic
• Activity recognition
• Support vector machine

Hinge-Loss Markov Random Fields and Probabilistic Soft Logic arXiv:1505.04406v2 [cs.LG] 9 DecStephen H. Bach∗ Matthias Broecheler† Bert Huang‡ Lise Getoor§

Source URL: stephenbach.net

• Logic
• Graphical models
• Mathematics
• Mathematical logic
• Structured prediction
• Markov random field
• Probability theory
• Non-classical logic
• Logic in computer science
• Bayesian network
• Random field
• Fuzzy logic