ML Anthology

JMLR 2009

93 papers

A Least-Squares Approach to Direct Importance Estimation Takafumi Kanamori, Shohei Hido, Masashi Sugiyama
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A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization Jacob Abernethy, Francis Bach, Theodoros Evgeniou, Jean-Philippe Vert
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A Parameter-Free Classification Method for Large Scale Learning Marc Boullé
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A Survey of Accuracy Evaluation Metrics of Recommendation Tasks Asela Gunawardana, Guy Shani
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Adaptive False Discovery Rate Control Under Independence and Dependence Gilles Blanchard, Étienne Roquain
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An Algorithm for Reading Dependencies from the Minimal Undirected Independence mAP of a Graphoid That Satisfies Weak Transitivity Jose M. Peña, Roland Nilsson, Johan Björkegren, Jesper Tegnér
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An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs M. Pawan Kumar, Vladimir Kolmogorov, Philip H.S. Torr
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An Anticorrelation Kernel for Subsystem Training in Multiple Classifier Systems Luciana Ferrer, Kemal Sönmez, Elizabeth Shriberg
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Analysis of Perceptron-Based Active Learning Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni
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Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification Eitan Greenshtein, Junyong Park
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Bayesian Network Structure Learning by Recursive Autonomy Identification Raanan Yehezkel, Boaz Lerner
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Bi-Level Path Following for Cross Validated Solution of Kernel Quantile Regression Saharon Rosset
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Bounded Kernel-Based Online Learning Francesco Orabona, Joseph Keshet, Barbara Caputo
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CarpeDiem: Optimizing the Viterbi Algorithm and Applications to Supervised Sequential Learning Roberto Esposito, Daniele P. Radicioni
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Cautious Collective Classification Luke K. McDowell, Kalyan Moy Gupta, David W. Aha
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Classification with Gaussians and Convex Loss Dao-Hong Xiang, Ding-Xuan Zhou
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Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors Mathias Drton, Michael Eichler, Thomas S. Richardson
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Consistency and Localizability Alon Zakai, Ya'acov Ritov
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Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm Junning Li, Z. Jane Wang
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Data-Driven Calibration of Penalties for Least-Squares Regression Sylvain Arlot, Pascal Massart
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Deterministic Error Analysis of Support Vector Regression and Related Regularized Kernel Methods Christian Rieger, Barbara Zwicknagl
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Discriminative Learning Under Covariate Shift Steffen Bickel, Michael Brückner, Tobias Scheffer
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Distance Metric Learning for Large Margin Nearest Neighbor Classification Kilian Q. Weinberger, Lawrence K. Saul
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Distributed Algorithms for Topic Models David Newman, Arthur Asuncion, Padhraic Smyth, Max Welling
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Efficient Online and Batch Learning Using Forward Backward Splitting John Duchi, Yoram Singer
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Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks Jean Hausser, Korbinian Strimmer
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Estimating Labels from Label Proportions Novi Quadrianto, Alex J. Smola, Tibério S. Caetano, Quoc V. Le
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Estimation of Sparse Binary Pairwise Markov Networks Using Pseudo-Likelihoods Holger Höfling, Robert Tibshirani
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Evolutionary Model Type Selection for Global Surrogate Modeling Dirk Gorissen, Tom Dhaene, Filip De Turck
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Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions Lisa Hellerstein, Bernard Rosell, Eric Bach, Soumya Ray, David Page
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Exploring Strategies for Training Deep Neural Networks Hugo Larochelle, Yoshua Bengio, Jérôme Louradour, Pascal Lamblin
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Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection Jie Chen, Haw-ren Fang, Yousef Saad
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Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination Eugene Tuv, Alexander Borisov, George Runger, Kari Torkkola
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Fourier Theoretic Probabilistic Inference over Permutations Jonathan Huang, Carlos Guestrin, Leonidas Guibas
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Generalization Bounds for Ranking Algorithms via Algorithmic Stability Shivani Agarwal, Partha Niyogi
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Hash Kernels for Structured Data Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alex Smola, S.V.N. Vishwanathan
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Hybrid MPI/OpenMP Parallel Linear Support Vector Machine Training Kristian Woodsend, Jacek Gondzio
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Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques Barnabás Póczos, András Loőrincz
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Improving the Reliability of Causal Discovery from Small Data Sets Using Argumentation Facundo Bromberg, Dimitris Margaritis
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Incorporating Functional Knowledge in Neural Networks Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René Garcia
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Learning Acyclic Probabilistic Circuits Using Test Paths Dana Angluin, James Aspnes, Jiang Chen, David Eisenstat, Lev Reyzin
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Learning Approximate Sequential Patterns for Classification Zeeshan Syed, Piotr Indyk, John Guttag
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Learning Halfspaces with Malicious Noise Adam R. Klivans, Philip M. Long, Rocco A. Servedio
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Learning Linear Ranking Functions for Beam Search with Application to Planning Yuehua Xu, Alan Fern, Sungwook Yoon
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Learning Nondeterministic Classifiers Juan José del Coz, Jorge Díez, Antonio Bahamonde
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Learning Permutations with Exponential Weights David P. Helmbold, Manfred K. Warmuth
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Learning When Concepts Abound Omid Madani, Michael Connor, Wiley Greiner
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Low-Rank Kernel Learning with Bregman Matrix Divergences Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
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Margin-Based Ranking and an Equivalence Between AdaBoost and RankBoost Cynthia Rudin, Robert E. Schapire
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Marginal Likelihood Integrals for Mixtures of Independence Models Shaowei Lin, Bernd Sturmfels, Zhiqiang Xu
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Markov Properties for Linear Causal Models with Correlated Errors Changsung Kang, Jin Tian
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Maximum Entropy Discrimination Markov Networks Jun Zhu, Eric P. Xing
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Multi-Task Reinforcement Learning in Partially Observable Stochastic Environments Hui Li, Xuejun Liao, Lawrence Carin
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Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions Sébastien Bubeck, Ulrike von Luxburg
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NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM Pradip Ghanty, Samrat Paul, Nikhil R. Pal
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Nonextensive Information Theoretic Kernels on Measures André F. T. Martins, Noah A. Smith, Eric P. Xing, Pedro M. Q. Aguiar, Mário A. T. Figueiredo
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Nonlinear Models Using Dirichlet Process Mixtures Babak Shahbaba, Radford Neal
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On Efficient Large Margin Semisupervised Learning: Method and Theory Junhui Wang, Xiaotong Shen, Wei Pan
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On the Consistency of Feature Selection Using Greedy Least Squares Regression Tong Zhang
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On the Power of Membership Queries in Agnostic Learning Vitaly Feldman
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On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality Wenxin Jiang
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Online Learning with Sample Path Constraints Shie Mannor, John N. Tsitsiklis, Jia Yuan Yu
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Online Learning with Samples Drawn from Non-Identical Distributions Ting Hu, Ding-Xuan Zhou
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Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization Vojtěch Franc, Sören Sonnenburg
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Particle Swarm Model Selection Hugo Jair Escalante, Manuel Montes, Luis Enrique Sucar
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Perturbation Corrections in Approximate Inference: Mixture Modelling Applications Ulrich Paquet, Ole Winther, Manfred Opper
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Polynomial-Delay Enumeration of Monotonic Graph Classes Jan Ramon, Siegfried Nijssen
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Prediction with Expert Advice for the Brier Game Vladimir Vovk, Fedor Zhdanov
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Properties of Monotonic Effects on Directed Acyclic Graphs Tyler J. VanderWeele, James M. Robins
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Provably Efficient Learning with Typed Parametric Models Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy
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Refinement of Reproducing Kernels Yuesheng Xu, Haizhang Zhang
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Reinforcement Learning in Finite MDPs: PAC Analysis Alexander L. Strehl, Lihong Li, Michael L. Littman
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Reproducing Kernel Banach Spaces for Machine Learning Haizhang Zhang, Yuesheng Xu, Jun Zhang
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Robust Process Discovery with Artificial Negative Events Stijn Goedertier, David Martens, Jan Vanthienen, Bart Baesens
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Robustness and Regularization of Support Vector Machines Huan Xu, Constantine Caramanis, Shie Mannor
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Scalable Collaborative Filtering Approaches for Large Recommender Systems Gábor Takács, István Pilászy, Bottyán Németh, Domonkos Tikk
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Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning Halbert White, Karim Chalak
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SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent Antoine Bordes, Léon Bottou, Patrick Gallinari
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Similarity-Based Classification: Concepts and Algorithms Yihua Chen, Eric K. Garcia, Maya R. Gupta, Ali Rahimi, Luca Cazzanti
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Sparse Online Learning via Truncated Gradient John Langford, Lihong Li, Tong Zhang
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Stable and Efficient Gaussian Process Calculations Leslie Foster, Alex Waagen, Nabeela Aijaz, Michael Hurley, Apolonio Luis, Joel Rinsky, Chandrika Satyavolu, Michael J. Way, Paul Gazis, Ashok Srivastava
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Strong Limit Theorems for the Bayesian Scoring Criterion in Bayesian Networks Nikolai Slobodianik, Dmitry Zaporozhets, Neal Madras
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Structure Spaces Brijnesh J. Jain, Klaus Obermayer
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Subgroup Analysis via Recursive Partitioning Xiaogang Su, Chih-Ling Tsai, Hansheng Wang, David M. Nickerson, Bogong Li
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Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining Petra Kralj Novak, Nada Lavrač, Geoffrey I. Webb
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The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models Ricardo Silva, Zoubin Ghahramani
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The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs Han Liu, John Lafferty, Larry Wasserman
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The P-Norm Push: A Simple Convex Ranking Algorithm That Concentrates at the Top of the List Cynthia Rudin
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Transfer Learning for Reinforcement Learning Domains: A Survey Matthew E. Taylor, Peter Stone
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Ultrahigh Dimensional Feature Selection: Beyond the Linear Model Jianqing Fan, Richard Samworth, Yichao Wu
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Universal Kernel-Based Learning with Applications to Regular Languages Leonid Kontorovich, Boaz Nadler
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Using Local Dependencies Within Batches to Improve Large Margin Classifiers Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, Bharat Rao
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When Is There a Representer Theorem? Vector Versus Matrix Regularizers Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil
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