PPT-Structured Perceptron

Alice Lai and Shi Zhi Presentation Outline Introduction to Structured Perceptron ILPCRF Model Averaged Perceptron Latent Variable Perceptron Motivation An algorithm to learn weights for structured prediction. 36 . of . 42. Machine Learning. : More ANNs,. Genetic and Evolutionary Computation (GEC). Discussion: . Genetic Programming. William H. Hsu. Department of Computing and Information Sciences, KSU. KSOL course page: . . The Black Queen Hypothesis . (Morris et al. 2012):. All biological functions have a cost. If all things are equal, excluding a function causes a fitness advantage. Products of ‘leaky’ biological functions are unavoidably made available to the community, . [slides prises du cours cs294-10 UC Berkeley (2006 / 2009)]. http://www.cs.berkeley.edu/~jordan/courses/294-fall09. Basic Classification in ML. !!!!$$$!!!!. Spam . filtering. Character. recognition. Input . Structured Training Program. The . DOTD . Structured Training Program . is a department-sanctioned, progressive training curriculum that requires specific work-related training be completed at each level of an employee’s career path. . Steve Branson . Oscar . Beijbom. . Serge . Belongie. CVPR 2013, Portland, Oregon. . UC San Diego. . UC San Diego. . Caltech. Overview. Structured prediction . Learning from larger datasets. conjunctions . the learner is to learn. The number of . conjunctions. : . . log(|C. |) = . n. The elimination algorithm makes . n. . mistakes. Learn from . positive . examples; eliminate active literals. conjunctions . the learner is to learn. The number of . conjunctions. : . . log(|C. |) = . n. The elimination algorithm makes . n. . mistakes. Learn from . positive . examples; eliminate active literals. Loomis Union School District. PBIS Coaches Institute. January 20, 2015. Disclaimer: . This is a Discussion Session. What has worked . at one of our sites. ?. What are some of the benefits?. What are some of the challenges?. Qingda Hu*, . Jinglei Ren. , Anirudh Badam, and Thomas Moscibroda. Microsoft Research. *Tsinghua University. Non-volatile memory is coming…. Data storage. 2. Read: ~50ns. Write: ~10GB/s. Read: ~10µs. Learning 2. Mike . Mozer. Department of Computer Science and. Institute of Cognitive Science. University of Colorado at Boulder. Review. Two learning rules. Hebbian. learning . regression. k!1) /19Proof of convergence10k!!|| k!1) k!1)+yixi"= Slobodan Vucetic * Vladimir Coric Zhuang Wang Department of Computer and Information Sciences Temple University Philadelphia, PA 19122, USA * t , y t ), t = 1…T}, where x t -dimensional inp approaches. John Larmouth. ITU-T and ISO/IEC ASN.1 Rapporteur. j.larmouth@btinternet.com. Terminology has changed over time. Markup. languages. Abstract. Syntax and Concrete Syntax. Abstract syntax notation and encodings. v. v. v. v. Shared weights. Filter = ‘local’ perceptron.. Also called . kernel.. Yann . LeCun’s. MNIST CNN architecture. DEMO. http://scs.ryerson.ca/~aharley/vis/conv/. Thanks to Adam Harley for making this..