Archive of AIRG papers

[BOTT97] Feb 1, 2002, by Marios Skounakis
Leon Bottou and Yann Le Cun and Yoshua Bengio, Global training of Document Processing Systems using Graph Transformer Networks

[BURG98] March 15, 2002, by Glenn Fung
Christopher J. C. Burges, A Tutorial on Support Vector Machines for Pattern Recognition

[DORI98] April 12, 2002, by Darryl Roy
Marco Dorigo and Thomas Stutzle, The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances

[ELID02] Sept 27, 2002, by Louis Oliphant
Elidan, Ninio, Friedman and Schuurmans, Data Perturbation for Escaping Local Maxima in Learning , AAAI 2002

[FRIE00] Oct 11, 2002, by Mark Rich
Frietag and Kushmerick, Boosted Wrapper Induction , AAAI 2000

[JAAK??] April 26, 2002, by Joe Bockhorst
Jaakola and Haussler, Exploiting Generative Models in Discriminative Classifiers

[JAAK??] April 26, 2002, by Joe Bockhorst
Jaakkola, Diekhans and Haussler, A Discriminative Framework for Detecting Remote Protein Homologies

[JOAC99] Dec 6, 2002, by Glenn Fung
Thorsten Joachims, Transductive Inference for Text Classification using Support Vector Machines , ICML 1999

[KRAM01] March 1, 2002, by Irene Ong
Kramer & Raedt, Feature Construction with Version Spaces for Biochemical Applications.

[MART02] Nov 8, 2002, by Sean McIlwain
Martelli, Fariselli, Krogh and Casadio, A sequence-profile-based HMM for predicting and discriminating beta barrel membrane proteins, ISMB 2002 (Best Paper Award)

[MUGG96] Feb 15, 2002, by Mark Rich
Stephen Muggleton, Stochastic Logic Programs

[MUGG00] Feb 15, 2002, by Mark Rich
Stephen Muggleton, Learning Stochastic Logic Programs

[SCHA98] Sept 13, 2002, by Somya Ray
Schapire, Freund, Bartlett and Lee, Boosting the margin: A new explanation for the effectiveness of voting methods

[SHAT00] Nov 22, 2002, by Michael Molla
Hagit Shatkay, Stephen Edwards, W. John Wilbur, and Mark Boguski, Genes, Themes and Microarrays Using Information Retrieval for Large-Scale Gene Analysis , ISMB 2000

[SRIN99] Oct 25, 2002, by Frank DiMaio
Ashwin Srinivasan, A study of two probabilistic methods for searching large spaces with ILP

[XING01] March 1, 2002, by Irene Ong
Xing, Jordan, and Karp, Feature selection for high dimensional genomic micro-array data.

October 2, 2003, by Soumya Ray
N. Littlestone, Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm

October 16, 2003, by Mark Goadrich
Lappoon R. Tang, Raymond J. Mooney, and Prem Melville, Scaling Up ILP to Large Examples: Results on Link Discovery for Counter-Terrorism

October 30, 2003, by Michael Waddell
James Allen and George Ferguson, Human-Machine Collaborative Planning

November 6, 2003, by Louis Oliphant
Mary Elaine Califf and Raymond J. Mooney, Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming

November 20, 2003, by Michael Schultz
Jeremey Buhler and Martin Tompa, Finding Motifs Using Random Projections and Antonis Rokas, Barry Williams, Nicole King and Sean Carroll, Genome-scale approaches to resolving incongruence in molecular phylogenies

December 4, 2003, by Beverly Seavy
Toshihiro Kamishima & Fumio Motoyahsi, Learning from Cluster Examples

October 12, 2005, by Jerry Zhu
Xiaojin Zhu, Jaz Kandola, John Lafferty, and Zoubin Ghahramani. Graph Kernels by Spectral Transforms. To appear in Semi-Supervised Learning, Chapelle, Schölkopf and Zien, eds. The MIT Press.

October 26, 2005, by Lisa Torrey
Kurt Driessens and Jan Ramon. Relational Instance Based Regression for Relational Reinforcement Learning. Proceedings of the 20th International Conference on Machine Learning, 2003.

November 9, 2005, by Ted Wild
Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu. The Entire Regularization Path for the Support Vector Machine. Advances in Neural Information Processing Systems 17, 2005

November 30, 2005, by Hector Corrada Bravo
Matthew Richardson and Pedro Domingos, Markov Logic Networks, Machine Learning, 2005

December 7, 2005, by Ted Wild
David M. Blei, Andrew Y. Ng, and Michael I. Jordan. Latent Dirichlet Allocation, Journal of Machine Learning Research 3, 2003

February 6, 2006, by Ted Wild
Janez Demšar. Statistical Comparisons of Classifiers over Multiple Data Sets, Journal of Machine Learning Research 7, 2006

February 24, 2006
Luke S. Zettlemoyer and Michael Collins. Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars, UAI 2005

March 10, 2006, by Pradheep Elango
Thomas Gartner. A Survey of Kernels for Structured Data, SIGKDD Explorations, 2003

March 24, 2006, by Jesse Davis
John M. Zelle, Raymond J. Mooney, and Joshua B. Konvisser. Combining Top-Down And Bottom-Up Techniques In Inductive Logic Programming, ML-94. Also S. Muggleton and W. Buntine. Machine invention of first-order predicates by inverting resolution. ICML 1988.

April 7, 2006, by Trevor Walker
Andrew G. Barto and Sridhar Mahadevan. Recent Advances in Hierarchical Reinforcement Learning

April 21, 2006, by Louis Oliphant
Rita Sharma and David Poole. Probabilistic Reasoning with Hierarchically Structured Variables, IJCAI 2005

May 5, 2006, by Keith Noto
Nir Friedman and Daphne Koller, Being Bayesian about Network Structure, UAI 2000.

May 24, 2006, by Frank DiMaio
Yedidia et al. Generalized Belief Propagation. NIPS 2000.

June 7, 2006, by Keith Noto
Won, Prugel-Bennet and Krogh. Evolving the Structure of Hidden Markov Models

June 21, 2006, by Lisa Torrey
S. Ben-David and R. Schuller. Exploiting task relatedness for multiple task learning. COLT 2003.

July 5, 2006, by Ted Wild
Wahba, G., Lin, Y. and Zhang, H. Generalized Approximate Cross Validation for Support Vector Machines, or, Another Way to Look at Margin-Like Quantities. (With revisions) in `Advances in Large Margin Classifiers, Smola, Bartlett, Scholkopf and Schurmans, eds., MIT Press (2000), 297-309.

July 19, 2006, by David Andrzejewski
Blei, D.M., Griffiths, T.L., Jordan, M.I., & Tenenbaum, J.B. (2004) Hierarchical topic models and the nested Chinese restaurant process. Advances in Neural Information Processing Systems 16.

August 16, 2006, by Jurgen Van Gael
Topic Modeling: Beyond Bag-of-Words. Also Latent Dirichlet Allocation.

August 30, 2006, by Mark Goadrich
Cost curves: An improved method for visualizing classifier performance by Chris Drummond and Robert C. Holte, Machine Learning, to appear.

September 25, 2006, by Frank Dimaio
Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs of Arbitrary Topology.

October 4, 2006, by Louis Oliphant
A Taxonomy of Global Optimization Methods Based on Response Surfaces.

October 18, 2006, by Ted Wild
Choosing between two learning algorithms based on calibrated tests.

November 1, 2006, by Trevor Walker
Predictive State Representations: A New Theory for Modeling Dynamical Systems.

November 15, 2006, by Adam Smith
Multiple Alignment of Continuous Time Series.

November 29, 2006, by Jurgen Van Gael
Chapter 2 from Gaussian Processes for Machine Learning.

December 13, 2006 by Ameet Soni
CONTRAfold: RNA secondary structure prediction without physics-based models.

January 31, 2007, by Louis Oliphant
On Discriminative vs. Generative classifiers: A comparison of logistic and Classification with Hybrid Generative/Discriminative Models.

February 14, 2007, by Lisa Torrey
Relating Reinforcement Learning Performance to Classification Performance.

March 14, 2007 by Ted Wild
Rule Extraction for Linear Support Vector Machines

September 17, 2007 by Ted Wild
Model selection for support vector machines via uniform design. The special issue on Machine Learning and Robust Data Mining of Computational Statistics and Data Analysis, 2006.

October 1, 2007 Héctor Corrada Bravo
Convex Optimization Techniques for Fitting Sparse Gaussian Graphical Models ICML 2006.

October 15, 2007 by Andrew Goldberg
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification ICML 2006.

November 5, 2007 by David Andrzejewski
Nonparametric Bayes Pachinko Allocation, UAI 2007.

November 12, 2007 by Lisa Torrey
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL, IJCAI 2007.

November 26, 2007 by Louis Oliphant
Searching for Interacting Features. IJCAI 2007.

December 10, 2007 by Chris Hinrichs
Spatial Latent Dirichlet Allocation. NIPS 2007.

February 13, 2008 by Héctor Corrada Bravo
Colored Maximum Variance Unfolding. NIPS 2007.

February 20, 2008 by Ted Wild
"Privacy-Preserving Support Vector Machines via Random Kernels".

March 5, 2008 by Sriraam Natarajan
Online Passive-Aggressive Algorithms. NIPS 2003.

March 26, 2008 by Ted Wild
Online Bayes Point Machines. Seventh Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 241-252, (2003).

April 9, 2008 by Lisa Torrey
WebCrow: a WEB-based system for CROssWord solving.AAAI 2005.

April 30, 2008 by David Andrzejewski
Non-redundant clustering with conditional ensembles. KDD '05.

May 7, 2008 by Louis Oliphant
Predicting Good Probabilities With Supervised Learning. ICML 2005.

September 15, 2008 by Eric Lantz
SVM Optimization: Inverse Dependence on Training Set Size. ICML 2008.

September 29, 2008 by David Andrzejewski
Beam Sampling for the Infinite Hidden Markov Model. ICML 2008.

October 13, 2008 by Burr Settles
Learning from Labeled Features using Generalized Expectation Criteria.SIGIR 2008.

November 10, 2008 by Andrew Goldberg
A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning. ICML 2008.

November 24, 2008 by Bess Berg
Boosted Bayesian Network Classifiers. Mach Learn (2008) 73: 155-184.

February 4, 2009 by Gautam Kunapuli
Model Selection via Bilevel Optimization. IJCNN '06. Extended Version.

February 18, 2009 by Andrew Goldberg
Large Scale Manifold Transduction. ICML 2008.

March 4, 2009 by Nate Fillmore
The Tradeoffs of Large Scale Learning. NIPS 2007.

March 11, 2009 by Chris Hinrichs
Robust Support Vector Machine Training via Convex Outlier Ablation. AAAI 2006.

April 1, 2009 by David Andrzejewski
Training Products of Experts by Minimizing Contrastive Divergence. Neural Computation 14, 1771-1800 (2002).

April 8, 2009 by Hidayath Ansari
Clustering with Local and Global Regularization. AAAI 2007.

April 22, 2009 by Lisa Torrey
Learning Classifiers from Only Positive and Unlabeled Data. KDD 2008.

September 16, 2009 by Junming Sui
On the relation between multi-instance learning and semi-supervised learning. ICML 07

September 30th, 2009 by Debbie Chasman
Uncertainty Sampling and Transductive Experimental Design for Active Dual Supervision. ICML 2009

October 14th, 2009 by Chris Hinrichs
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers. CVPR 2009

October 28th, 2009 by Kendrick Boyd
Learning Markov Logic Network Structure via Hypergraph Lifting. ICML 2009

November 11th, 2009 by Ameet Soni
Supervised Learning from Multiple Experts: Whom to trust when everyone lies a bit. ICML 2009

Februrary 10th, 2010 by Bryan Gibson
DUOL: A Double Updating Approach for Online Learning NIPS 2009

Februrary 24th, 2010 by Kwang-Sun Jun
Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process SDM 2008

March 10th, 2010 by Andrew Goldberg
Semi-Supervised Sequence Modeling with Syntactic Topic Models AAAI 2005

March 24th, 2010 by Ameet Soni
Model Selection: Beyond the Bayesian/Frequentist Divide JMLR 2010

April 7th, 2010 by Suhail Shergill
Bayesian Algorithms for Causal Data Mining JMLR 2010

September 29th, 2010 by Chris Hinrichs
Proximal Methods for Sparse Hierarchical Dictionary Learning ICML 2010

October 13th, 2010 by Suhail Shergill
Structured Ranking Learning using Cumulative Distribution Networks NIPS 2009

October 27th, 2010 by Debbie Chasman
Occam's Two Razors: The Sharp and the Blunt KDD 1998

November 10th, 2010 by Bryan Gibson
PAC generalization bounds for co-training NIPS 2001

December 8th, 2010 by Andreas Vlachos
A Multi-Pass Sieve for Coreference Resolution EMNLP 2010

March 2nd, 2011 by Junming Sui
When Is There a Representer Theorem? Vector Versus Matrix Regularizers JMLR 2009

March 30th, 2011 by Kwang-Sung Jun
Modeling Dynamic Data with Binary Latent Factors NIPS 2008

April 13th, 2011 by Andreas Vlachos
Learning semantic correspondences with less supervision ACL-IJCNLP 2009

April 27th, 2011 by Chris Hinrichs
Maximum Relative Margin and Data-Dependent Regularization JLMR 2010