JMLR Volume 11
- An Efficient Explanation of Individual Classifications using Game Theory
- Erik Štrumbelj, Igor Kononenko; 11(Jan):1−18, 2010.
[abs][pdf]
- Online Learning for Matrix Factorization and Sparse Coding
- Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro; 11(Jan):19−60, 2010.
[abs][pdf]
- Model Selection: Beyond the Bayesian/Frequentist Divide
- Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin Cawley; 11(Jan):61−87, 2010.
[abs][pdf]
- On-Line Sequential Bin Packing
- András György, Gábor Lugosi, György Ottucsàk; 11(Jan):89−109, 2010.
[abs][pdf]
- Classification Methods with Reject Option Based on Convex Risk Minimization
- Ming Yuan, Marten Wegkamp; 11(Jan):111−130, 2010.
[abs][pdf]
- An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data
- Yufeng Ding, Jeffrey S. Simonoff; 11(Jan):131−170, 2010.
[abs][pdf]
- Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation
- Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos; 11(Jan):171−234, 2010.
[abs][pdf][erratum]
- Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions
- Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos; 11(Jan):235−284, 2010.
[abs][pdf]
- Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure
- Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru Miyano; 11(Jan):285−310, 2010.
[abs][pdf]
- Bundle Methods for Regularized Risk Minimization
- Choon Hui Teo, S.V.N. Vishwanthan, Alex J. Smola, Quoc V. Le; 11(Jan):311−365, 2010.
[abs][pdf]
- A Convergent Online Single Time Scale Actor Critic Algorithm
- Dotan Di Castro, Ron Meir; 11(Jan):367−410, 2010.
[abs][pdf]
- Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
- Philippos Mordohai, Gérard Medioni; 11(Jan):411−450, 2010.
[abs][pdf]
- Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization
- Jarkko Venna, Jaakko Peltonen, Kristian Nybo, Helena Aidos, Samuel Kaski; 11(Feb):451−490, 2010.
[abs][pdf]
- Classification Using Geometric Level Sets
- Kush R. Varshney, Alan S. Willsky; 11(Feb):491−516, 2010.
[abs][pdf]
- Generalized Power Method for Sparse Principal Component Analysis
- Michel Journée, Yurii Nesterov, Peter Richtárik, Rodolphe Sepulchre; 11(Feb):517−553, 2010.
[abs][pdf]
- Approximate Tree Kernels
- Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Robert Müller; 11(Feb):555−580, 2010.
[abs][pdf]
- On Finding Predictors for Arbitrary Families of Processes
- Daniil Ryabko; 11(Feb):581−602, 2010.
[abs][pdf]
- A Rotation Test to Verify Latent Structure
- Patrick O. Perry, Art B. Owen; 11(Feb):603−624, 2010.
[abs][pdf]
- Why Does Unsupervised Pre-training Help Deep Learning?
- Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio; 11(Feb):625−660, 2010.
[abs][pdf]
- Error-Correcting Output Codes Library
- Sergio Escalera, Oriol Pujol, Petia Radeva; 11(Feb):661−664, 2010.
[abs][pdf] [code][mloss.org]
- Second-Order Bilinear Discriminant Analysis
- Christoforos Christoforou, Robert Haralick, Paul Sajda, Lucas C. Parra; 11(Feb):665−685, 2010.
[abs][pdf]
- On the Rate of Convergence of the Bagged Nearest Neighbor Estimate
- Gérard Biau, Frédéric Cérou, Arnaud Guyader; 11(Feb):687−712, 2010.
[abs][pdf]
- A Fast Hybrid Algorithm for Large-Scale l1-Regularized Logistic Regression
- Jianing Shi, Wotao Yin, Stanley Osher, Paul Sajda; 11(Feb):713−741, 2010.
[abs][pdf]
- PyBrain
- Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber; 11(Feb):743−746, 2010.
[abs][pdf] [code][mloss.org]
- Maximum Relative Margin and Data-Dependent Regularization
- Pannagadatta K. Shivaswamy, Tony Jebara; 11(Feb):747−788, 2010.
[abs][pdf]
- Stability Bounds for Stationary φ-mixing and β-mixing Processes
- Mehryar Mohri, Afshin Rostamizadeh; 11(Feb):789−814, 2010.
[abs][pdf]
- Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
- Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin; 11(Feb):815−848, 2010.
[abs][pdf]
- A Streaming Parallel Decision Tree Algorithm
- Yael Ben-Haim, Elad Tom-Tov; 11(Feb):849−872, 2010.
[abs][pdf]
- Image Denoising with Kernels Based on Natural Image Relations
- Valero Laparra, Juan Gutiérrez, Gustavo Camps-Valls, Jesús Malo; 11(Feb):873−903, 2010.
[abs][pdf]
- On Learning with Integral Operators
- Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito; 11(Feb):905−934, 2010.
[abs][pdf]
- On Spectral Learning
- Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil; 11(Feb):935−953, 2010.
[abs][pdf]
- Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
- Gideon S. Mann, Andrew McCallum; 11(Feb):955−984, 2010.
[abs][pdf]
- Kronecker Graphs: An Approach to Modeling Networks
- Jure Leskovec, Deepayan Chakrabarti, Jon Kleinberg, Christos Faloutsos, Zoubin Ghahramani; 11(Feb):985−1042, 2010.
[abs][pdf]
- Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes
- Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwright; 11(Mar):1043−1080, 2010.
[abs][pdf]
- Analysis of Multi-stage Convex Relaxation for Sparse Regularization
- Tong Zhang; 11(Mar):1081−1107, 2010.
[abs][pdf]
- Large Scale Online Learning of Image Similarity Through Ranking
- Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio; 11(Mar):1109−1135, 2010.
[abs][pdf]
- Continuous Time Bayesian Network Reasoning and Learning Engine
- Christian R. Shelton, Yu Fan, William Lam, Joon Lee, Jing Xu; 11(Mar):1137−1140, 2010.
[abs][pdf] [code][mloss.org]
- SFO: A Toolbox for Submodular Function Optimization
- Andreas Krause; 11(Mar):1141−1144, 2010.
[abs][pdf] [code][mloss.org]
- A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
- Jin Yu, S.V.N. Vishwanathan, Simon Güunter, Nicol N. Schraudolph; 11(Mar):1145−1200, 2010.
[abs][pdf]
- Graph Kernels
- S.V.N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt; 11(Apr):1201−1242, 2010.
[abs][pdf][erratum]
- Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
- Miki Aoyagi; 11(Apr):1243−1272, 2010.
[abs][pdf]
- Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation
- Vicenç Gómez, Hilbert J. Kappen, Michael Chertkov; 11(Apr):1273−1296, 2010.
[abs][pdf]
- Learning From Crowds
- Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Gerardo Hermosillo Valadez, Charles Florin, Luca Bogoni, Linda Moy; 11(Apr):1297−1322, 2010.
[abs][pdf]
- Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
- Pinar Donmez, Guy Lebanon, Krishnakumar Balasubramanian; 11(Apr):1323−1351, 2010.
[abs][pdf]
- Learning Translation Invariant Kernels for Classification
- Kamaledin Ghiasi-Shirazi, Reza Safabakhsh, Mostafa Shamsi; 11(Apr):1353−1390, 2010.
[abs][pdf]
- Consistent Nonparametric Tests of Independence
- Arthur Gretton, László Györfi; 11(Apr):1391−1423, 2010.
[abs][pdf]
- Characterization, Stability and Convergence of Hierarchical Clustering Methods
- Gunnar Carlsson, Facundo Mémoli; 11(Apr):1425−1470, 2010.
[abs][pdf]
- Training and Testing Low-degree Polynomial Data Mappings via Linear SVM
- Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Michael Ringgaard, Chih-Jen Lin; 11(Apr):1471−1490, 2010.
[abs][pdf]
- Quadratic Programming Feature Selection
- Irene Rodriguez-Lujan, Ramon Huerta, Charles Elkan, Carlos Santa Cruz; 11(Apr):1491−1516, 2010.
[abs][pdf]
- Hilbert Space Embeddings and Metrics on Probability Measures
- Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R.G. Lanckriet; 11(Apr):1517−1561, 2010.
[abs][pdf]
- Near-optimal Regret Bounds for Reinforcement Learning
- Thomas Jaksch, Ronald Ortner, Peter Auer; 11(Apr):1563−1600, 2010.
[abs][pdf]
- MOA: Massive Online Analysis
- Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer; 11(May):1601−1604, 2010.
[abs][pdf] [code][mloss.org]
- On the Foundations of Noise-free Selective Classification
- Ran El-Yaniv, Yair Wiener; 11(May):1605−1641, 2010.
[abs][pdf]
- Introduction to Causal Inference
- Peter Spirtes; 11(May):1643−1662, 2010.
[abs][pdf]
- Consensus-Based Distributed Support Vector Machines
- Pedro A. Forero, Alfonso Cano, Georgios B. Giannakis; 11(May):1663−1707, 2010.
[abs][pdf]
- Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
- Aapo Hyvärinen, Kun Zhang, Shohei Shimizu, Patrik O. Hoyer; 11(May):1709−1731, 2010.
[abs][pdf]
- FastInf: An Efficient Approximate Inference Library
- Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan; 11(May):1733−1736, 2010.
[abs][pdf] [code][mloss.org]
- Evolving Static Representations for Task Transfer
- Phillip Verbancsics, Kenneth O. Stanley; 11(May):1737−1769, 2010.
[abs][pdf]
- Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing
- Ryo Yoshida, Mike West; 11(May):1771−1798, 2010.
[abs][pdf]
- The SHOGUN Machine Learning Toolbox
- Sören Sonnenburg, Gunnar Rätsch, Sebastian Henschel, Christian Widmer, Jonas Behr, Alexander Zien, Fabio de Bona, Alexander Binder, Christian Gehl, Vojtěch Franc; 11(Jun):1799−1802, 2010.
[abs][pdf] [code][mloss.org]
- How to Explain Individual Classification Decisions
- David Baehrens, Timon Schroeter, Stefan Harmeling, Motoaki Kawanabe, Katja Hansen, Klaus-Robert Müller; 11(Jun):1803−1831, 2010.
[abs][pdf]
- Permutation Tests for Studying Classifier Performance
- Markus Ojala, Gemma C. Garriga; 11(Jun):1833−1863, 2010.
[abs][pdf]
- Sparse Spectrum Gaussian Process Regression
- Miguel Lázaro-Gredilla, Joaquin Quiñonero-Candela, Carl Edward Rasmussen, Aníbal R. Figueiras-Vidal; 11(Jun):1865−1881, 2010.
[abs][pdf]
- Fast and Scalable Local Kernel Machines
- Nicola Segata, Enrico Blanzieri; 11(Jun):1883−1926, 2010.
[abs][pdf]
- Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary β-Mixing Processes
- Liva Ralaivola, Marie Szafranski, Guillaume Stempfel; 11(Jul):1927−1956, 2010.
[abs][pdf]
- Practical Approaches to Principal Component Analysis in the Presence of Missing Values
- Alexander Ilin, Tapani Raiko; 11(Jul):1957−2000, 2010.
[abs][pdf]
- Posterior Regularization for Structured Latent Variable Models
- Kuzman Ganchev, João Graça, Jennifer Gillenwater, Ben Taskar; 11(Jul):2001−2049, 2010.
[abs][pdf]
- A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
- Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom Dhaene, Karel Crombecq; 11(Jul):2051−2055, 2010.
[abs][pdf] [code][mloss.org]
- Matrix Completion from Noisy Entries
- Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh; 11(Jul):2057−2078, 2010.
[abs][pdf]
- On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
- Gavin C. Cawley, Nicola L. C. Talbot; 11(Jul):2079−2107, 2010.
[abs][pdf]
- Model-based Boosting 2.0
- Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner; 11(Aug):2109−2113, 2010.
[abs][pdf] [code][mloss.org]
- Importance Sampling for Continuous Time Bayesian Networks
- Yu Fan, Jing Xu, Christian R. Shelton; 11(Aug):2115−2140, 2010.
[abs][pdf]
- Matched Gene Selection and Committee Classifier for Molecular Classification of Heterogeneous Diseases
- Guoqiang Yu, Yuanjian Feng, David J. Miller, Jianhua Xuan, Eric P. Hoffman, Robert Clarke, Ben Davidson, Ie-Ming Shih, Yue Wang; 11(Aug):2141−2167, 2010.
[abs][pdf]
- libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models
- Joris M. Mooij; 11(Aug):2169−2173, 2010.
[abs][pdf] [code][mloss.org]
- Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
- Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mukherjee; 11(Aug):2175−2198, 2010.
[abs][pdf]
- Regularized Discriminant Analysis, Ridge Regression and Beyond
- Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jordan; 11(Aug):2199−2228, 2010.
[abs][pdf]
- Erratum: SGDQN is Less Careful than Expected
- Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan Chang, S. Alex Smith; 11(Aug):2229−2240, 2010.
[abs][pdf]
- Restricted Eigenvalue Properties for Correlated Gaussian Designs
- Garvesh Raskutti, Martin J. Wainwright, Bin Yu; 11(Aug):2241−2259, 2010.
[abs][pdf]
- High Dimensional Inverse Covariance Matrix Estimation via Linear Programming
- Ming Yuan; 11(Aug):2261−2286, 2010.
[abs][pdf]
- Spectral Regularization Algorithms for Learning Large Incomplete Matrices
- Rahul Mazumder, Trevor Hastie, Robert Tibshirani; 11(Aug):2287−2322, 2010.
[abs][pdf]
- Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
- Franz Pernkopf, Jeff A. Bilmes; 11(Aug):2323−2360, 2010.
[abs][pdf]
- High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency
- Dapo Omidiran, Martin J. Wainwright; 11(Aug):2361−2386, 2010.
[abs][pdf]
- Composite Binary Losses
- Mark D. Reid, Robert C. Williamson; 11(Sep):2387−2422, 2010.
[abs][pdf]
- Sparse Semi-supervised Learning Using Conjugate Functions
- Shiliang Sun, John Shawe-Taylor; 11(Sep):2423−2455, 2010.
[abs][pdf]
- Rademacher Complexities and Bounding the Excess Risk in Active Learning
- Vladimir Koltchinskii; 11(Sep):2457−2485, 2010.
[abs][pdf]
- Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
- Miloš Radovanović, Alexandros Nanopoulos, Mirjana Ivanović; 11(Sep):2487−2531, 2010.
[abs][pdf]
- WEKA−Experiences with a Java Open-Source Project
- Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten; 11(Sep):2533−2541, 2010.
[abs][pdf]
- Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization
- Lin Xiao; 11(Oct):2543−2596, 2010.
[abs][pdf]
- Stochastic Composite Likelihood
- Joshua V. Dillon, Guy Lebanon; 11(Oct):2597−2633, 2010.
[abs][pdf]
- Learnability, Stability and Uniform Convergence
- Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan; 11(Oct):2635−2670, 2010.
[abs][pdf]
- Topology Selection in Graphical Models of Autoregressive Processes
- Jitkomut Songsiri, Lieven Vandenberghe; 11(Oct):2671−2705, 2010.
[abs][pdf]
- Using Contextual Representations to Efficiently Learn Context-Free Languages
- Alexander Clark, Rémi Eyraud, Amaury Habrard; 11(Oct):2707−2744, 2010.
[abs][pdf]
- Mean Field Variational Approximation for Continuous-Time Bayesian Networks
- Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman; 11(Oct):2745−2783, 2010.
[abs][pdf]
- Regret Bounds and Minimax Policies under Partial Monitoring
- Jean-Yves Audibert, Sébastien Bubeck; 11(Oct):2785−2836, 2010.
[abs][pdf]
- Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
- Nguyen Xuan Vinh, Julien Epps, James Bailey; 11(Oct):2837−2854, 2010.
[abs][pdf]
- Expectation Truncation and the Benefits of Preselection In Training Generative Models
- Jörg Lücke, Julian Eggert; 11(Oct):2855−2900, 2010.
[abs][pdf]
- Linear Algorithms for Online Multitask Classification
- Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile; 11(Oct):2901−2934, 2010.
[abs][pdf]
- Tree Decomposition for Large-Scale SVM Problems
- Fu Chang, Chien-Yang Guo, Xiao-Rong Lin, Chi-Jen Lu; 11(Oct):2935−2972, 2010.
[abs][pdf]
- Semi-Supervised Novelty Detection
- Gilles Blanchard, Gyemin Lee, Clayton Scott; 11(Nov):2973−3009, 2010.
[abs][pdf]
- Gaussian Processes for Machine Learning (GPML) Toolbox
- Carl Edward Rasmussen, Hannes Nickisch; 11(Nov):3011−3015, 2010.
[abs][pdf] [code][mloss.org]
- Covariance in Unsupervised Learning of Probabilistic Grammars
- Shay B. Cohen, Noah A. Smith; 11(Nov):3017−3051, 2010.
[abs][pdf]
- Inducing Tree-Substitution Grammars
- Trevor Cohn, Phil Blunsom, Sharon Goldwater; 11(Nov):3053−3096, 2010.
[abs][pdf]
- Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials
- Rahul Gupta, Sunita Sarawagi, Ajit A. Diwan; 11(Nov):3097−3135, 2010.
[abs][pdf]
- A Generalized Path Integral Control Approach to Reinforcement Learning
- Evangelos Theodorou, Jonas Buchli, Stefan Schaal; 11(Nov):3137−3181, 2010.
[abs][pdf][erratum]
- A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification
- Guo-Xun Yuan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin; 11(Nov):3183−3234, 2010.
[abs][pdf]
- Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
- Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen; 11(Nov):3235−3268, 2010.
[abs][pdf]
- Classification with Incomplete Data Using Dirichlet Process Priors
- Chunping Wang, Xuejun Liao, Lawrence Carin, David B. Dunson; 11(Dec):3269−3311, 2010.
[abs][pdf]
- Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
- Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra; 11(Dec):3313−3332, 2010.
[abs][pdf]
- Learning Instance-Specific Predictive Models
- Shyam Visweswaran, Gregory F. Cooper; 11(Dec):3333−3369, 2010.
[abs][pdf]
- Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
- Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol; 11(Dec):3371−3408, 2010.
[abs][pdf]
- Lp-Nested Symmetric Distributions
- Fabian Sinz, Matthias Bethge; 11(Dec):3409−3451, 2010.
[abs][pdf]
- Efficient Algorithms for Conditional Independence Inference
- Remco Bouckaert, Raymond Hemmecke, Silvia Lindner, Milan Studený; 11(Dec):3453−3479, 2010.
[abs][pdf]
- An Exponential Model for Infinite Rankings
- Marina Meilă, Le Bao; 11(Dec):3481−3518, 2010.
[abs][pdf]
- Rate Minimaxity of the Lasso and Dantzig Selector for the lq Loss in lr Balls
- Fei Ye, Cun-Hui Zhang; 11(Dec):3519−3540, 2010.
[abs][pdf]
- Incremental Sigmoid Belief Networks for Grammar Learning
- James Henderson, Ivan Titov; 11(Dec):3541−3570, 2010.
[abs][pdf]
- Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory
- Sumio Watanabe; 11(Dec):3571−3594, 2010.
[abs][pdf]
- PAC-Bayesian Analysis of Co-clustering and Beyond
- Yevgeny Seldin, Naftali Tishby; 11(Dec):3595−3646, 2010.
[abs][pdf]
- Learning Non-Stationary Dynamic Bayesian Networks
- Joshua W. Robinson, Alexander J. Hartemink; 11(Dec):3647−3680, 2010.
[abs][pdf]
