Tutorial on Online User Engagement: Metrics and Optimization
These are the slides of the tutorial Liangjie Hong and I gave at The Web Conference in San Francisco, 2019. Full details of the tutorial and previous instances can be found at https://onlineuserengagement.github.io/. Tutorial abstract: User engagement plays a central role in companies operating online services, such as search engines, news portals, e commerce sites, entertainment services, and soc
A Brief Beginner’s Guide To Clojure
by John Gabriele, last-modified: 2016-06 (using Clojure 1.8.0, Leiningen 2.6.1, and OpenJDK 8) The purpose of this brief guide is to provide new users with a 1000-meter view of Clojure and its ecosystem, including how to quickly get up and running. This guide concerns the original, Java-based Clojure implementation (though, there are others). It’s not a Clojure language tutorial; there are a numbe
cplusplus.com - The C++ resources network
Tutorials C++ Language: Learn this versatile and powerful programming language. Includes detailed explanations of pointers, functions, classes and templates, among others... Reference Description of the most important classes, functions and objects of the Standard Language Library, with descriptive fully-functional short programs as examples. Browse the C++ Reference Articles User-contributed arti
Map/Reduce Tutorial
This document comprehensively describes all user-facing facets of the Hadoop Map/Reduce framework and serves as a tutorial. Ensure that Hadoop is installed, configured and is running. More details: Hadoop Quick Start for first-time users. Hadoop Cluster Setup for large, distributed clusters. Hadoop Map/Reduce is a software framework for easily writing applications which process vast amounts of
Semi-Supervised Learning Tutorial
Semi-Supervised Learning Tutorial Xiaojin Zhu Department of Computer Sciences University of Wisconsin, Madison, USA ICML 2007 Xiaojin Zhu (Univ. Wisconsin, Madison) Semi-Supervised Learning Tutorial ICML 2007 1 / 135 Outline 1 Introduction to Semi-Supervised Learning 2 Semi-Supervised Learning Algorithms Self Training Generative Models S3VMs Graph-Based Algorithms Multiview Algorithms 3 Semi-Super
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Discourse Structure - Theory, Practice and Use
https://people.eecs.berkeley.edu/~jordan/nips-tutorial05.ps
NIPS*03 One-day Workshop on Nonparametric Bayesian methods and Infinite models
mlrg:papers:factorgraphs.pdf - Machine Learning Research Group
Tailoring Word Alignments to Syntactic Machine Translation
Microsoft PowerPoint - BPtutorial.ppt
Tutorial on Factor Graph and Belief Propagation References: Factor Graphs and the Sum-Product Algorithm by Frank R. Kschischang, Brendan J. Frey, and Hans-Andrea Loeliger, IT Trans. Feb. 2001 Constructing Free Energy Approximations and Generalized Belief
https://people.eecs.berkeley.edu/~klein/papers/tutorial-acl2007.pdf
WWW2009
http://pages.cs.wisc.edu/~goldberg/publications/goldbergTextgraphs.pdf
http://pages.cs.wisc.edu/~goldberg/publications/sslnlp_realisticSSL.pdf
http://www.pletscher.org/academics/undergraduate/talks/lda-slides.pdf
Feature-based Distributed Language Modeling with a Mixture of Experts
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