Papers by Year

2009

• Xiaojin Zhu and Andrew B. Goldberg. Introduction to Semi-Supervised Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2009.
• Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, Rakesh Agrawal, Panayiotis Tsaparas, John Shafer. Improving classification accuracy using automatically extracted training data. 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Industrial Track (KDD 2009).
• Andrew B. Goldberg and Xiaojin Zhu. Keepin' it real: Semi-supervised learning with realistic tuning. NAACL 2009 Workshop on Semi-supervised Learning for NLP (NAACL-SSLNLP 2009). [PDF slides]
• Arthur Glenberg, Andrew B. Goldberg, and Xiaojin Zhu. Improving early reading comprehension using embodied CAI. Instructional Science, 2009.
• Andrew B. Goldberg, Nathanael Fillmore, David Andrzejewski, Zhiting Xu, Bryan Gibson and Xiaojin Zhu. May All Your Wishes Come True: A Study of Wishes and How to Recognize Them Annual Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT 2009). [data | PDF slides]
• Andrew B. Goldberg, Xiaojin Zhu, Aarti Singh, Zhiting Xu, and Robert Nowak. Multi-manifold semi-supervised learning. Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS 2009). [PDF poster]
• Xiaojin Zhu, Andrew B. Goldberg, and Tushar Khot. Some new directions in graph-based semisupervised learning (invited paper). IEEE International Conference on Multimedia and Expo (ICME), Special Session on Semi-Supervised Learning for Multimedia Analysis, 2009.
• Andrew B. Goldberg, Jake Rosin, Xiaojin Zhu, and Charles R. Dyer. Toward Text-to-Picture Synthesis. NIPS 2009 Symposium on Assistive Machine Learning for People with Disabilities, 2009.

2008

• Andrew B. Goldberg, Ming Li, and Xiaojin Zhu. Online Manifold Regularization: A New Learning Setting and Empirical Study. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2008). [PDF poster | PDF slides]
• Andrew B. Goldberg, Xiaojin Zhu, Charles R. Dyer, Mohamed Eldawy, and Lijie Heng. Easy as ABC? Facilitating pictorial communication via semantically enhanced layout. Twelfth Conference on Computational Natural Language Learning (CoNLL 2008). [PDF slides]
• Jerry Zhu, Andrew B. Goldberg, Michael Rabbat, and Robert Nowak. Learning bigrams from unigrams. 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL 2008). [PDF slides]

2007

• Jerry Zhu, Andrew B. Goldberg, Mohamed Eldawy, Charles Dyer, and Bradley Strock. A text-to-picture synthesis system for augmenting communication. The Integrated Intelligence Track of the Twenty-Second AAAI Conference on Artificial Intelligence (AAAI 2007).
• Jerry Zhu and Andrew B. Goldberg. Kernel regression with order preferences. Twenty-Second AAAI Conference on Artificial Intelligence (AAAI 2007). (Also see technical report version below.)
• Jerry Zhu, Andrew B. Goldberg, Jurgen Van Gael, David Andrzejewski. Improving Diversity in Ranking using Absorbing Random Walks. Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL 2007).
• Andrew B. Goldberg, Jerry Zhu, and Stephen Wright. Dissimilarity in Graph-Based Semi-Supervised Classification. Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS 2007).

2006

• Andrew B. Goldberg, David Andrzejewski, Jurgen Van Gael, Burr Settles, Xiaojin Zhu, and Mark Craven. Ranking Biomedical Passages for Relevance and Diversity: University of Wisconsin, Madison at TREC Genomics 2006. Proceedings of the Fifteenth Text Retrieval Conference (TREC 2006). [PDF slides | PDF poster]
• Andrew B. Goldberg and Jerry Zhu. Semi-supervised Regression with Order Preferences. Computer Sciences TR 1578, University of Wisconsin - Madison.
• Andrew B. Goldberg and Jerry Zhu. Seeing stars when there aren't many stars: Graph-based semi-supervised learning for sentiment categorization. HLT-NAACL 2006 Workshop on Textgraphs: Graph-based Algorithms for Natural Language Processing. [PDF slides]

Miscellaneous Lecture Notes & Slides

• Class lecture on manifold regularization and the paper "Beyond the point cloud: from transductive to semi-supervised learning" by Sindhwani, Niyogi, and Belkin.
• Automatic Summarization: notes discussing supervised and unsupervised approaches to keyphrase extraction and document summarization. Prepared for a guest lecture in CS 769 (Advanced NLP) (formerly CS 838) and makes reference to the summarization-related papers listed on that course Web site. [Notes | Slides]

Undergraduate Thesis

• Andrew B. Goldberg. Highly Constrained Sports Scheduling With Genetic Algorithms. Senior Thesis. Amherst College, 2003.

Books

• Xiaojin Zhu and Andrew B. Goldberg. Introduction to Semi-Supervised Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2009.
• Deitel, Harvey M., Paul J. Deitel, and Andrew B. Goldberg. Internet & World Wide Web How to Program. 3rd ed. Upper Saddle River, NJ: Prentice Hall, 2003. [Publisher site | Amazon.com]