Buoyant Mixtures of Cellular Automaton Gases. - Christopher J. C. Burges; Stéphane Zaleski (Complex Syst., 1987)

A neural network approach to handprint character recognition. - Lawrence D. Jackel; Charles E. Stenard; Henry S. Baird; Bernhard E. Boser; Jane Bromley; Christopher J. C. Burges; John S. Denker; Hans Peter Graf; Donnie Henderson; Richard E. Howard; Wayne E. Hubbard; Yann LeCun; et al. (Compcon, 1991)

Multi-Digit Recognition Using a Space Displacement Neural Network. - Ofer Matan; Christopher J. C. Burges; Yann LeCun; John S. Denker (NIPS, 1991)

Reading Handwritten Digits: A ZIP Code Recognition System. - Ofer Matan; Henry S. Baird; Jane Bromley; Christopher J. C. Burges; John S. Denker; Lawrence D. Jackel; Yann LeCun; Edwin P. D. Pednault; William Satterfield; Charles E. Stenard; Timothy J. Thompson (Computer, 1992)

Off Line Recognition of Handwritten Postal Words Using Neural Networks. - Christopher J. C. Burges; Jan Ben; John S. Denker; Yann LeCun; Craig R. Nohl (Int. J. Pattern Recognit. Artif. Intell., 1993)

Analysis of complex and noisy check images. - Hans Peter Graf; Christopher J. C. Burges; Eric Cosatto; Craig R. Nohl (ICIP (3), 1995)

Extracting Support Data for a Given Task. - Bernhard Schölkopf; Chris Burges; Vladimir Vapnik (KDD, 1995)

LeRec: a NN/HMM hybrid for on-line handwriting recognition. - Yoshua Bengio; Yann LeCun; Craig R. Nohl; Christopher J. C. Burges (Neural Comput., 1995)

Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models. - Volker Blanz; Bernhard Schölkopf; Heinrich H. Bülthoff; Chris Burges; Vladimir Vapnik; Thomas Vetter (ICANN, 1996)

Incorporating Invariances in Support Vector Learning Machines. - Bernhard Schölkopf; Chris Burges; Vladimir Vapnik (ICANN, 1996)

Simplified Support Vector Decision Rules. - Christopher J. C. Burges (ICML, 1996)

Improving the Accuracy and Speed of Support Vector Machines. - Christopher J. C. Burges; Bernhard Schölkopf (NIPS, 1996)

Support Vector Regression Machines. - Harris Drucker; Christopher J. C. Burges; Linda Kaufman; Alexander J. Smola; Vladimir Vapnik (NIPS, 1996)

Comparing support vector machines with Gaussian kernels to radial basis function classifiers. - Bernhard Schölkopf; Kah Kay Sung; Christopher J. C. Burges; Federico Girosi; Partha Niyogi; Tomaso A. Poggio; Vladimir Vapnik (IEEE Trans. Signal Process., 1997)

Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces. - Bernhard Schölkopf; Alexander J. Smola; Phil Knirsch; Chris Burges (DAGM-Symposium, 1998)

A Tutorial on Support Vector Machines for Pattern Recognition. - Christopher J. C. Burges (Data Min. Knowl. Discov., 1998)

Distinctive feature detection using support vector machines. - Partha Niyogi; Chris Burges; Padma Ramesh (ICASSP, 1999)

Uniqueness of the SVM Solution. - Christopher J. C. Burges; David J. Crisp (NIPS, 1999)

A Geometric Interpretation of v-SVM Classifiers. - David J. Crisp; Christopher J. C. Burges (NIPS, 1999)

Discussion on the paper by Friedman and Fisher. - Chris Burges (Stat. Comput., 1999)

Input space versus feature space in kernel-based methods. - Bernhard Schölkopf; Sebastian Mika; Christopher J. C. Burges; Phil Knirsch; Klaus-Robert Müller; Gunnar Rätsch; Alexander J. Smola (IEEE Trans. Neural Networks, 1999)

Improving Wavelet Compression with Neural Networks. - Christopher J. C. Burges; Patrice Y. Simard; Henrique S. Malvar (Data Compression Conference, 2001)

Learning a Gaussian Process Prior for Automatically Generating Music Playlists. - John C. Platt; Christopher J. C. Burges; Steven Swenson; Christopher Weare; Alice Zheng (NIPS, 2001)

Extracting noise-robust features from audio data. - Christopher J. C. Burges; John C. Platt; Soumya Jana (ICASSP, 2002)

Editorial: Kernel Methods: Current Research and Future Directions. - Nello Cristianini; Colin Campbell; Chris Burges (Mach. Learn., 2002)

Some Notes on Applied Mathematics for Machine Learning. - Christopher J. C. Burges (Advanced Lectures on Machine Learning, 2003)

Image compression with on-line and off-line learning. - Patrice Y. Simard; Christopher J. C. Burges; David Steinkraus; Henrique S. Malvar (ICIP (2), 2003)

Identifying audio clips with RARE. - Christopher J. C. Burges; John C. Platt; Jonathan Goldstein (ACM Multimedia, 2003)

Uniqueness theorems for kernel methods. - Christopher J. C. Burges; David J. Crisp (Neurocomputing, 2003)

Distortion discriminant analysis for audio fingerprinting. - Christopher J. C. Burges; John C. Platt; Soumya Jana (IEEE Trans. Speech Audio Process., 2003)

Redundant Bit Vectors for Quickly Searching High-Dimensional Regions. - Jonathan Goldstein; John C. Platt; Christopher J. C. Burges (Deterministic and Statistical Methods in Machine Learning, 2004)

Convolutional networks for speech detection. - Somsak Sukittanon; Arun C. Surendran; John C. Platt; Christopher J. C. Burges (INTERSPEECH, 2004)

Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour. - Christopher J. C. Burges (The Data Mining and Knowledge Discovery Handbook, 2005)

Using audio fingerprinting for duplicate detection and thumbnail generation. - Christopher J. C. Burges; Dan Plastina; John C. Platt; Erin Renshaw; Henrique S. Malvar (ICASSP (3), 2005)

Learning to rank using gradient descent. - Christopher J. C. Burges; Tal Shaked; Erin Renshaw; Ari Lazier; Matt Deeds; Nicole Hamilton; Gregory N. Hullender (ICML, 2005)

Inferring similarity between music objects with application to playlist generation. - Robert Ragno; Christopher J. C. Burges; Cormac Herley (Multimedia Information Retrieval, 2005)

Semi-Supervised Learning with Conditional Harmonic Mixing. - Christopher J. C. Burges; John C. Platt (Semi-Supervised Learning, 2006)

Optimisation methods for ranking functions with multiple parameters. - Michael J. Taylor 001; Hugo Zaragoza; Nick Craswell; Stephen Robertson; Chris Burges (CIKM, 2006)

Learning to Rank with Nonsmooth Cost Functions. - Christopher J. C. Burges; Robert Ragno; Quoc Viet Le (NIPS, 2006)

High accuracy retrieval with multiple nested ranker. - Irina Matveeva; Chris Burges; Timo Burkard; Andy Laucius; Leon Wong (SIGIR, 2006)

Improving Web Spam Classification using Rank-time Features. - Krysta M. Svore; Qiang Wu; Chris Burges; Aaswath Pattabhi Raman (AIRWeb, 2007)

Transductive Link Spam Detection. - Dengyong Zhou; Chris Burges; Tao Tao (AIRWeb, 2007)

Enhancing Single-Document Summarization by Combining RankNet and Third-Party Sources. - Krysta M. Svore; Lucy Vanderwende; Christopher J. C. Burges (EMNLP-CoNLL, 2007)

Spectral clustering and transductive learning with multiple views. - Dengyong Zhou; Christopher J. C. Burges (ICML, 2007)

McRank: Learning to Rank Using Multiple Classification and Gradient Boosting. - Ping Li 001; Christopher J. C. Burges; Qiang Wu (NIPS, 2007)

Question Answering over Implicitly Structured Web Content. - Eugene Agichtein; Chris Burges; Eric Brill (Web Intelligence, 2007)

Using Signals of Human Interest to Enhance Single-document Summarization. - Krysta M. Svore; Lucy Vanderwende; Christopher J. C. Burges (AAAI, 2008)

A machine learning approach for improved BM25 retrieval. - Krysta M. Svore; Christopher J. C. Burges (CIKM, 2009)

Model Adaptation via Model Interpolation and Boosting for Web Search Ranking. - Jianfeng Gao 001; Qiang Wu; Chris Burges; Krysta M. Svore; Yi Su; Nazan Khan; Shalin Shah; Hongyan Zhou (EMNLP, 2009)

On the local optimality of LambdaRank. - Pinar Donmez; Krysta M. Svore; Christopher J. C. Burges (SIGIR, 2009)

Dimension Reduction: A Guided Tour. - Christopher J. C. Burges (Found. Trends Mach. Learn., 2010)

Adapting boosting for information retrieval measures. - Qiang Wu; Christopher J. C. Burges; Krysta M. Svore; Jianfeng Gao 001 (Inf. Retr., 2010)

Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour. - Christopher J. C. Burges (Data Mining and Knowledge Discovery Handbook, 2010)

Learning to rank with multiple objective functions. - Krysta M. Svore; Maksims Volkovs; Christopher J. C. Burges (WWW, 2011)

Learning to Rank Using an Ensemble of Lambda-Gradient Models. - Christopher J. C. Burges; Krysta M. Svore; Paul N. Bennett; Andrzej Pastusiak; Qiang Wu (Yahoo! Learning to Rank Challenge, 2011)

Computational Approaches to Sentence Completion. - Geoffrey Zweig; John C. Platt; Christopher Meek; Christopher J. C. Burges; Ainur Yessenalina; Qiang Liu 001 (ACL (1), 2012)

Learning from mistakes: towards a correctable learning algorithm. - Karthik Raman 001; Krysta M. Svore; Ran Gilad-Bachrach; Christopher J. C. Burges (CIKM, 2012)

A Challenge Set for Advancing Language Modeling. - Geoffrey Zweig; Christopher J. C. Burges (WLM@NAACL-HLT, 2012)

The Median Hypothesis. - Ran Gilad-Bachrach; Christopher J. C. Burges (Empirical Inference, 2013)

Animacy Detection with Voting Models. - Joshua L. Moore; Christopher J. C. Burges; Erin Renshaw; Wen-tau Yih (EMNLP, 2013)

MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text. - Matthew Richardson; Christopher J. C. Burges; Erin Renshaw (EMNLP, 2013)

Classifier selection using the predicate depth. - Ran Gilad-Bachrach; Christopher J. C. Burges (J. Mach. Learn. Res., 2013)

Relations World: A Possibilistic Graphical Model. - Christopher J. C. Burges; Erin Renshaw; Andrzej Pastusiak (CoRR, 2014)

A Base Camp for Scaling AI. - Christopher J. C. Burges; Ted Hart; Zi Yang; Silviu-Petru Cucerzan; Ryen W. White; Andrzej Pastusiak; Julia Lewis (CoRR, 2016)