MLJ 2012

51 papers

An Alternative View of Variational Bayes and Asymptotic Approximations of Free Energy Kazuho Watanabe

Applying the Information Bottleneck to Statistical Relational Learning Fabrizio Riguzzi, Nicola Di Mauro

Bayesian Multi-Instance Multi-Label Learning Using Gaussian Process Prior Jianjun He, Hong Gu, Zhelong Wang

Bridging Logic and Kernel Machines Michelangelo Diligenti, Marco Gori, Marco Maggini, Leonardo Rigutini

Compressed Labeling on Distilled Labelsets for Multi-Label Learning Tianyi Zhou, Dacheng Tao, Xindong Wu

Data and Task Parallelism in ILP Using MapReduce Ashwin Srinivasan, Tanveer A. Faruquie, Sachindra Joshi

Efficient Cross-Validation for Kernelized Least-Squares Regression with Sparse Basis Expansions Tapio Pahikkala, Hanna Suominen, Jorma Boberg

Efficient Max-Margin Multi-Label Classification with Applications to Zero-Shot Learning Bharath Hariharan, S. V. N. Vishwanathan, Manik Varma

Efficiently Identifying Deterministic Real-Time Automata from Labeled Data Sicco Verwer, Mathijs de Weerdt, Cees Witteveen

Experiment Databases - A New Way to Share, Organize and Learn from Experiments Joaquin Vanschoren, Hendrik Blockeel, Bernhard Pfahringer, Geoffrey Holmes

Focused Multi-Task Learning in a Gaussian Process Framework Gayle Leen, Jaakko Peltonen, Samuel Kaski

Generating Feature Spaces for Linear Algorithms with Regularized Sparse Kernel Slow Feature Analysis Wendelin Böhmer, Steffen Grünewälder, Hannes Nickisch, Klaus Obermayer

Good Edit Similarity Learning by Loss Minimization Aurélien Bellet, Amaury Habrard, Marc Sebban

Gradient-Based Boosting for Statistical Relational Learning: The Relational Dependency Network Case Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik

How to Reverse-Engineer Quality Rankings Allison Chang, Cynthia Rudin, Michael Cavaretta, Robert Thomas, Gloria Chou

ILP Turns 20 - Biography and Future Challenges Stephen H. Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan

Inverse Subsumption for Complete Explanatory Induction Yoshitaka Yamamoto, Katsumi Inoue, Koji Iwanuma

K-Optimal: A Novel Approximate Inference Algorithm for ProbLog Joris Renkens, Guy Van den Broeck, Siegfried Nijssen

Learning by Extrapolation from Marginal to Full-Multivariate Probability Distributions: Decreasingly Naive Bayesian Classification Geoffrey I. Webb, Janice R. Boughton, Fei Zheng, Kai Ming Ting, Houssam Salem

Learning Compact Markov Logic Networks with Decision Trees Hassan Khosravi, Oliver Schulte, Jianfeng Hu, Tianxiang Gao

Learning Directed Relational Models with Recursive Dependencies Oliver Schulte, Hassan Khosravi, Tong Man

Learning Graphical Models for Relational Data via Lattice Search Oliver Schulte, Hassan Khosravi

Learning Monotone Nonlinear Models Using the Choquet Integral Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier

Learning Sparse Gradients for Variable Selection and Dimension Reduction Gui-Bo Ye, Xiaohui Xie

Linear Classifiers Are Nearly Optimal When Hidden Variables Have Diverse Effects Nader H. Bshouty, Philip M. Long

Local Equivalences of Distances Between Clusterings - A Geometric Perspective Marina Meila

Meta-Learning for Evolutionary Parameter Optimization of Classifiers Matthias Reif, Faisal Shafait, Andreas Dengel

Multi-Output Learning via Spectral Filtering Luca Baldassarre, Lorenzo Rosasco, Annalisa Barla, Alessandro Verri

Multi-Parametric Solution-Path Algorithm for Instance-Weighted Support Vector Machines Masayuki Karasuyama, Naoyuki Harada, Masashi Sugiyama, Ichiro Takeuchi

Multilabel Classification with Meta-Level Features in a Learning-to-Rank Framework Yiming Yang, Siddharth Gopal

Novel High Intrinsic Dimensionality Estimators Alessandro Rozza, Gabriele Lombardi, Claudio Ceruti, Elena Casiraghi, Paola Campadelli

On Label Dependence and Loss Minimization in Multi-Label Classification Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier

Online Bayesian Inference for the Parameters of PRISM Programs James Cussens

Online Variance Minimization Manfred K. Warmuth, Dima Kuzmin

Optimal Control as a Graphical Model Inference Problem Hilbert J. Kappen, Vicenç Gómez, Manfred Opper

PAMR: Passive Aggressive Mean Reversion Strategy for Portfolio Selection Bin Li, Peilin Zhao, Steven C. H. Hoi, Vivekanand Gopalkrishnan

Preference-Based Reinforcement Learning: A Formal Framework and a Policy Iteration Algorithm Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park

RE-EM Trees: A Data Mining Approach for Longitudinal and Clustered Data Rebecca J. Sela, Jeffrey S. Simonoff

Relational Networks of Conditional Preferences Frédéric Koriche

Robustness and Generalization Huan Xu, Shie Mannor

ROC Convex Hull and Nonparametric Maximum Likelihood Estimation Johan Lim, Joong-Ho Won

Scalable and Efficient Multi-Label Classification for Evolving Data Streams Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer

Sequential Approaches for Learning Datum-Wise Sparse Representations Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari

Similarity Measures over Refinement Graphs Santiago Ontañón, Enric Plaza

Statistical Analysis of Kernel-Based Least-Squares Density-Ratio Estimation Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama

Statistical Topic Models for Multi-Label Document Classification Timothy N. Rubin, America Chambers, Padhraic Smyth, Mark Steyvers

Structured Learning with Constrained Conditional Models Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth

Subsumption Resolution: An Efficient and Effective Technique for Semi-Naive Bayesian Learning Fei Zheng, Geoffrey I. Webb, Pramuditha Suraweera, Liguang Zhu

Synergy of Multi-Label Hierarchical Ensembles, Data Fusion, and Cost-Sensitive Methods for Gene Functional Inference Nicolò Cesa-Bianchi, Matteo Re, Giorgio Valentini

Temporal-Difference Search in Computer Go David Silver, Richard S. Sutton, Martin Müller

Visualizing Non-Metric Similarities in Multiple Maps Laurens van der Maaten, Geoffrey E. Hinton