- Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby:
Euclidean Embedding of Co-occurrence Data. J. Mach. Learn. Res. 8: 2265-2295 (2007) - Vicenç Gómez, Joris M. Mooij, Hilbert J. Kappen:
Truncating the Loop Series Expansion for Belief Propagation. J. Mach. Learn. Res. 8: 1987-2016 (2007) - Kristen Grauman, Trevor Darrell:
The Pyramid Match Kernel: Efficient Learning with Sets of Features. J. Mach. Learn. Res. 8: 725-760 (2007) - Yann Guermeur:
VC Theory of Large Margin Multi-Category Classifiers. J. Mach. Learn. Res. 8: 2551-2594 (2007) - Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan:
Fast Iterative Kernel Principal Component Analysis. J. Mach. Learn. Res. 8: 1893-1918 (2007) - András György, Tamás Linder, Gábor Lugosi, György Ottucsák:
The On-Line Shortest Path Problem Under Partial Monitoring. J. Mach. Learn. Res. 8: 2369-2403 (2007) - Onur C. Hamsici, Aleix M. Martínez:
Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification. J. Mach. Learn. Res. 8: 1583-1623 (2007) - Matthias Hein, Jean-Yves Audibert, Ulrike von Luxburg:
Graph Laplacians and their Convergence on Random Neighborhood Graphs. J. Mach. Learn. Res. 8: 1325-1368 (2007) - Ray J. Hickey:
Structure and Majority Classes in Decision Tree Learning. J. Mach. Learn. Res. 8: 1747-1768 (2007) - Carine Hue, Marc Boullé:
A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning. J. Mach. Learn. Res. 8: 2727-2754 (2007) - Zakria Hussain, François Laviolette, Mario Marchand, John Shawe-Taylor, S. Charles Brubaker, Matthew D. Mullin:
Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data. J. Mach. Learn. Res. 8: 2533-2549 (2007) - Rie Johnson, Tong Zhang:
On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning. J. Mach. Learn. Res. 8: 1489-1517 (2007) - Markus Kalisch, Peter Bühlmann:
Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm. J. Mach. Learn. Res. 8: 613-636 (2007) - Roni Khardon, Gabriel Wachman:
Noise Tolerant Variants of the Perceptron Algorithm. J. Mach. Learn. Res. 8: 227-248 (2007) - Kwangmoo Koh, Seung-Jean Kim, Stephen P. Boyd:
An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression. J. Mach. Learn. Res. 8: 1519-1555 (2007) - J. Zico Kolter, Marcus A. Maloof:
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts. J. Mach. Learn. Res. 8: 2755-2790 (2007) - Moshe Koppel, Jonathan Schler, Elisheva Bonchek-Dokow:
Measuring Differentiability: Unmasking Pseudonymous Authors. J. Mach. Learn. Res. 8: 1261-1276 (2007) - Dima Kuzmin, Manfred K. Warmuth:
Unlabeled Compression Schemes for Maximum Classes. J. Mach. Learn. Res. 8: 2047-2081 (2007) - Niels Landwehr, Kristian Kersting, Luc De Raedt:
Integrating Naïve Bayes and FOIL. J. Mach. Learn. Res. 8: 481-507 (2007) - François Laviolette, Mario Marchand:
PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers. J. Mach. Learn. Res. 8: 1461-1487 (2007) - Guy Lebanon, Yi Mao, Joshua V. Dillon:
The Locally Weighted Bag of Words Framework for Document Representation. J. Mach. Learn. Res. 8: 2405-2441 (2007) - Ping Li, Trevor Hastie, Kenneth Ward Church:
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections. J. Mach. Learn. Res. 8: 2497-2532 (2007) - Jia Li, Surajit Ray, Bruce G. Lindsay:
A Nonparametric Statistical Approach to Clustering via Mode Identification. J. Mach. Learn. Res. 8: 1687-1723 (2007) - Nikolas List, Hans Ulrich Simon:
General Polynomial Time Decomposition Algorithms. J. Mach. Learn. Res. 8: 303-321 (2007) - Chao-Chun Liu, Dao-Qing Dai, Hong Yan:
Local Discriminant Wavelet Packet Coordinates for Face Recognition. J. Mach. Learn. Res. 8: 1165-1195 (2007) - Marco Loog:
A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion. J. Mach. Learn. Res. 8: 2121-2123 (2007) - Gaëlle Loosli, Stéphane Canu:
Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets". J. Mach. Learn. Res. 8: 291-301 (2007) - Sofus A. Macskassy, Foster J. Provost:
Classification in Networked Data: A Toolkit and a Univariate Case Study. J. Mach. Learn. Res. 8: 935-983 (2007) - Sridhar Mahadevan, Mauro Maggioni:
Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes. J. Mach. Learn. Res. 8: 2169-2231 (2007) - David Mease, Abraham J. Wyner, Andreas Buja:
Boosted Classification Trees and Class Probability/Quantile Estimation. J. Mach. Learn. Res. 8: 409-439 (2007)