Xiaojin (Jerry) Zhu

Associate Professor of Computer Science

University of Wisconsin-Madison

Courses

Spring 2012: CS761 Advanced Machine Learning

• Advanced computational approaches to learning. Quantification of learnability and rate of learning, probabilistic and other formalisms of learning, statistical and computational analysis of learning models, state-of-the-art learning algorithms.

Fall 2012: CS540 Introduction to Artificial Intelligence

• Explore the fascinating world of artificial intelligence! This is the undergraduate AI course. Topics include search, logic, probabilistic inference, decision trees, neural networks, support vector machines, and game theory.

CS769 Advanced Natural Language Processing

• This graduate course covers statistical methods for processing natural text. Some questions discussed in class: How does Google work? How many bits are there in each English word? Can your computer learn to laugh at a joke? Did Shakespeare write this book? Where did "The vodka is good, but the meat is rotten" come from?

Tutorials

• Tutorial on All of Graphical Models at The tenth International Conference on Machine Learning and Applications (ICMLA11), 2011.
• Tutorial on Semi-Supervised Learning at University of Chicago Machine Learning Summer School 2009
• Tutorial on Semi-Supervised Learning for Natural Language Processing at ACL 2008 with John Blitzer
• Tutorial on Semi-Supervised Learning at ICML 2007
• Tutorial and practice session on Semi-Supervised Classification: learning from labeled and unlabeled data at AERFAI Summer School. Granada, 2006

Talks

Conference and workshop presentations not included -- they can be found on the publications web page.

• Machine Learning Theory by the People, for the People, of the People, Machine Learning and Applications Seminar, Purdue, 2011
• Adding Domain Knowledge to Latent Topic Models, University of Massachusetts Amherst, 2011
• Is Machine Learning the Wrong Name?, Boston University, 2010
• Computers Discover Wishes and Creativity in Text, Indiana University-Purdue University Indianapolis, 2009
• HAMLET, IBM, 2009
• Semi-Supervised Learning by Multi-Manifold Separation, IMA Minnesota, 2008
• Text-to-Picture Synthesis, Carnegie Mellon University, 2008
• Online Semi-Supervised Learning, 40th Symposium on the Interface: Computing Science and Statistics, 2008
• Semi-Supervised Learning in Computers and Humans, University of Michigan--Ann Arbor, 2007
• Semi-Supervised Learning: an overview, Joint Statistical Meetings, Seattle, Washington, 2006

Local seminars

• HAMLET (Human, Animal, and Machine Learning: Experiment and Theory)
• Fall 2011 Meet the AI Group (organized by Bryan Gibson).
• Spring 2011 Structured Sparsity Reading Group (organized by Junming Xu).
• Fall 2010 Non-i.i.d. Learning Reading Group (organized by Kwang-Sung Jun).
• Spring 2010 Learning Math for Machine Learning (LMML) Reading Group (organized by David Andrzejewski)
• Fall 2009 Bayesian Nonparametrics Reading Group (organized by Andrew Goldberg)

Random stuff

• Excellent, free museums within walking distance on campus:
  • Geology Museum: fossils & minerals
  • Chazen Museum of Art: paintings & sculpture
  • L.R. Ingersoll Physics Museum: hands-on physics
• Not sure how to pronounce Chinese names like Zhu, Cai, Qin, Xu? Learn it in five minutes
• Build a spectroscope from a CD and a cereal box