ML Anthology

JMLR 2012

104 papers

A Case Study on Meta-Generalising: A Gaussian Processes Approach Grigorios Skolidis, Guido Sanguinetti
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A Comparison of the Lasso and Marginal Regression Christopher R. Genovese, Jiashun Jin, Larry Wasserman, Zhigang Yao
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A Geometric Approach to Sample Compression Benjamin I.P. Rubinstein, J. Hyam Rubinstein
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A Kernel Two-Sample Test Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander Smola
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A Local Spectral Method for Graphs: With Applications to Improving Graph Partitions and Exploring Data Graphs Locally Michael W. Mahoney, Lorenzo Orecchia, Nisheeth K. Vishnoi
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A Model of the Perception of Facial Expressions of Emotion by Humans: Research Overview and Perspectives Aleix Martinez, Shichuan Du
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A Multi-Stage Framework for Dantzig Selector and LASSO Ji Liu, Peter Wonka, Jieping Ye
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A Primal-Dual Convergence Analysis of Boosting Matus Telgarsky
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A Unified View of Performance Metrics: Translating Threshold Choice into Expected Classification Loss José Hernández-Orallo, Peter Flach, Cèsar Ferri
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A Unifying Probabilistic Perspective for Spectral Dimensionality Reduction: Insights and New Models Neil D. Lawrence
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Active Clustering of Biological Sequences Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia
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Active Learning via Perfect Selective Classification Ran El-Yaniv, Yair Wiener
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Activized Learning: Transforming Passive to Active with Improved Label Complexity Steve Hanneke
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Algebraic Geometric Comparison of Probability Distributions Franz J. Király, Paul von Bünau, Frank C. Meinecke, Duncan A.J. Blythe, Klaus-Robert Müller
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Algorithms for Learning Kernels Based on Centered Alignment Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
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An Active Learning Algorithm for Ranking from Pairwise Preferences with an Almost Optimal Query Complexity Nir Ailon
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An Improved GLMNET for L1-Regularized Logistic Regression Guo-Xun Yuan, Chia-Hua Ho, Chih-Jen Lin
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An Introduction to Artificial Prediction Markets for Classification Adrian Barbu, Nathan Lay
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Analysis of a Random Forests Model Gérard Biau
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Bayesian Mixed-Effects Inference on Classification Performance in Hierarchical Data Sets Kay H. Brodersen, Christoph Mathys, Justin R. Chumbley, Jean Daunizeau, Cheng Soon Ong, Joachim M. Buhmann, Klaas E. Stephan
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Bounding the Probability of Error for High Precision Optical Character Recognition Gary B. Huang, Andrew Kae, Carl Doersch, Erik Learned-Miller
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Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training Zhuang Wang, Koby Crammer, Slobodan Vucetic
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Causal Bounds and Observable Constraints for Non-Deterministic Models Roland R. Ramsahai
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Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs Alain Hauser, Peter Bühlmann
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Coherence Functions with Applications in Large-Margin Classification Methods Zhihua Zhang, Dehua Liu, Guang Dai, Michael I. Jordan
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Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luján
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Confidence-Weighted Linear Classification for Text Categorization Koby Crammer, Mark Dredze, Fernando Pereira
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Consistent Model Selection Criteria on High Dimensions Yongdai Kim, Sunghoon Kwon, Hosik Choi
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Discriminative Hierarchical Part-Based Models for Human Parsing and Action Recognition Yang Wang, Duan Tran, Zicheng Liao, David Forsyth
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Distance Metric Learning with Eigenvalue Optimization Yiming Ying, Peng Li
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Dynamic Policy Programming Mohammad Gheshlaghi Azar, Vicenç Gómez, Hilbert J. Kappen
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Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya, Arkadi Nemirovski
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Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks Vikas C. Raykar, Shipeng Yu
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Entropy Search for Information-Efficient Global Optimization Philipp Hennig, Christian J. Schuler
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EP-GIG Priors and Applications in Bayesian Sparse Learning Zhihua Zhang, Shusen Wang, Dehua Liu, Michael I. Jordan
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Estimation and Selection via Absolute Penalized Convex Minimization and Its Multistage Adaptive Applications Jian Huang, Cun-Hui Zhang
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Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso Rahul Mazumder, Trevor Hastie
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Exploration in Relational Domains for Model-Based Reinforcement Learning Tobias Lang, Marc Toussaint, Kristian Kersting
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Facilitating Score and Causal Inference Trees for Large Observational Studies Xiaogang Su, Joseph Kang, Juanjuan Fan, Richard A. Levine, Xin Yan
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Fast Approximation of Matrix Coherence and Statistical Leverage Petros Drineas, Malik Magdon-Ismail, Michael W. Mahoney, David P. Woodruff
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Feature Selection via Dependence Maximization Le Song, Alex Smola, Arthur Gretton, Justin Bedo, Karsten Borgwardt
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Finding Recurrent Patterns from Continuous Sign Language Sentences for Automated Extraction of Signs Sunita Nayak, Kester Duncan, Sudeep Sarkar, Barbara Loeding
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Finite-Sample Analysis of Least-Squares Policy Iteration Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
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High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion Animashree Anandkumar, Vincent Y.F. Tan, Furong Huang, Alan S. Willsky
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Hope and Fear for Discriminative Training of Statistical Translation Models David Chiang
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Human Gesture Recognition on Product Manifolds Yui Man Lui
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Integrating a Partial Model into Model Free Reinforcement Learning Aviv Tamar, Dotan Di Castro, Ron Meir
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Iterative Reweighted Algorithms for Matrix Rank Minimization Karthik Mohan, Maryam Fazel
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Large-Scale Linear Support Vector Regression Chia-Hua Ho, Chih-Jen Lin
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Learning Algorithms for the Classification Restricted Boltzmann Machine Hugo Larochelle, Michael Mandel, Razvan Pascanu, Yoshua Bengio
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Learning Linear Cyclic Causal Models with Latent Variables Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
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Learning Symbolic Representations of Hybrid Dynamical Systems Daniel L. Ly, Hod Lipson
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Linear Fitted-Q Iteration with Multiple Reward Functions Daniel J. Lizotte, Michael Bowling, Susan A. Murphy
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Linear Regression with Random Projections Odalric-Ambrym Maillard, Rémi Munos
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Local and Global Scaling Reduce Hubs in Space Dominik Schnitzer, Arthur Flexer, Markus Schedl, Gerhard Widmer
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Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-Features Gil Tahan, Lior Rokach, Yuval Shahar
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Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning Sangkyun Lee, Stephen J. Wright
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MedLDA: Maximum Margin Supervised Topic Models Jun Zhu, Amr Ahmed, Eric P. Xing
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Metric and Kernel Learning Using a Linear Transformation Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon
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Minimax Manifold Estimation Christopher Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry Wasserman
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Minimax-Optimal Rates for Sparse Additive Models over Kernel Classes via Convex Programming Garvesh Raskutti, Martin J. Wainwright, Bin Yu
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Mixability Is Bayes Risk Curvature Relative to Log Loss Tim van Erven, Mark D. Reid, Robert C. Williamson
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Multi Kernel Learning with Online-Batch Optimization Francesco Orabona, Luo Jie, Barbara Caputo
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Multi-Assignment Clustering for Boolean Data Mario Frank, Andreas P. Streich, David Basin, Joachim M. Buhmann
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Multi-Instance Learning with Any Hypothesis Class Sivan Sabato, Naftali Tishby
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Multi-Target Regression with Rule Ensembles Timo Aho, Bernard Ženko, Sašo Džeroski, Tapio Elomaa
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Multi-Task Regression Using Minimal Penalties Matthieu Solnon, Sylvain Arlot, Francis Bach
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Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics Michael U. Gutmann, Aapo Hyvärinen
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Non-Sparse Multiple Kernel Fisher Discriminant Analysis Fei Yan, Josef Kittler, Krystian Mikolajczyk, Atif Tahir
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Nonparametric Guidance of Autoencoder Representations Using Label Information Jasper Snoek, Ryan P. Adams, Hugo Larochelle
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On Ranking and Generalization Bounds Wojciech Rejchel
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On the Convergence Rate of Lp-Norm Multiple Kernel Learning Marius Kloft, Gilles Blanchard
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On the Necessity of Irrelevant Variables David P. Helmbold, Philip M. Long
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Online Learning in the Embedded Manifold of Low-Rank Matrices Uri Shalit, Daphna Weinshall, Gal Chechik
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Online Submodular Minimization Elad Hazan, Satyen Kale
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Optimal Distributed Online Prediction Using Mini-Batches Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao
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Optimistic Bayesian Sampling in Contextual-Bandit Problems Benedict C. May, Nathan Korda, Anthony Lee, David S. Leslie
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PAC-Bayes Bounds with Data Dependent Priors Emilio Parrado-Hernández, Amiran Ambroladze, John Shawe-Taylor, Shiliang Sun
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Pairwise Support Vector Machines and Their Application to Large Scale Problems Carl Brunner, Andreas Fischer, Klaus Luig, Thorsten Thies
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Plug-in Approach to Active Learning Stanislav Minsker
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Positive Semidefinite Metric Learning Using Boosting-like Algorithms Chunhua Shen, Junae Kim, Lei Wang, Anton van den Hengel
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Quantum Set Intersection and Its Application to Associative Memory Tamer Salman, Yoram Baram
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Query Strategies for Evading Convex-Inducing Classifiers Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Steven J. Lee, Satish Rao, J. D. Tygar
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Random Search for Hyper-Parameter Optimization James Bergstra, Yoshua Bengio
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Refinement of Operator-Valued Reproducing Kernels Haizhang Zhang, Yuesheng Xu, Qinghui Zhang
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Regularization Techniques for Learning with Matrices Sham M. Kakade, Shai Shalev-Shwartz, Ambuj Tewari
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Regularized Bundle Methods for Convex and Non-Convex Risks Trinh Minh Tri Do, Thierry Artières
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Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise Sahand Negahban, Martin J. Wainwright
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Robust Kernel Density Estimation JooSeuk Kim, Clayton D. Scott
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Sampling Methods for the Nystr M Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
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Security Analysis of Online Centroid Anomaly Detection Marius Kloft, Pavel Laskov
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Selective Sampling and Active Learning from Single and Multiple Teachers Ofer Dekel, Claudio Gentile, Karthik Sridharan
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Sign Language Recognition Using Sub-Units Helen Cooper, Eng-Jon Ong, Nicolas Pugeault, Richard Bowden
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Smoothing Multivariate Performance Measures Xinhua Zhang, Ankan Saha, S.V.N. Vishwanathan
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Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing Nicolas Gillis
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Stability of Density-Based Clustering Alessandro Rinaldo, Aarti Singh, Rebecca Nugent, Larry Wasserman
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Static Prediction Games for Adversarial Learning Problems Michael Brückner, Christian Kanzow, Tobias Scheffer
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Structured Sparsity and Generalization Andreas Maurer, Massimiliano Pontil
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Structured Sparsity via Alternating Direction Methods Zhiwei Qin, Donald Goldfarb
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Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies Ioannis Tsamardinos, Sofia Triantafillou, Vincenzo Lagani
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Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints Mehrdad Mahdavi, Rong Jin, Tianbao Yang
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Transfer in Reinforcement Learning via Shared Features George Konidaris, Ilya Scheidwasser, Andrew Barto
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Variable Selection in High-Dimensional Varying-Coefficient Models with Global Optimality Lan Xue, Annie Qu
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Variational Multinomial Logit Gaussian Process Kian Ming A. Chai
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