Journal of Machine Learning Research, Vol. 15 Tahun 2014
1.) Bridging Viterbi and Posterior Decoding: A Generalized Risk Approach to Hidden Path Inference Based on Hidden Markov Models. --Jüri Lember, Alexey A. Koloydenko.
2.) Fast SVM Training Using Approximate Extreme Points. --Manu Nandan, Pramod P. Khargonekar, Sachin S. Talathi.
3.) Detecting Click Fraud in Online Advertising: A Data Mining Approach. --Richard Oentaryo, Ee-Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Minh Nhut Nguyen, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar.
4.) EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines. --Marc Claesen, Frank De Smet, Johan A.K. Suykens, Bart De Moor.
5.) A Junction Tree Framework for Undirected Graphical Model Selection. --Divyanshu Vats, Robert D. Nowak.
6.) Axioms for Graph Clustering Quality Functions. --Twan van Laarhoven, Elena Marchiori.
7.) Convex vs Non-Convex Estimators for Regression and Sparse Estimation: the Mean Squared Error Properties of ARD and GLasso. --Aleksandr Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto.
8.) Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning. --Aaron Wilson, Alan Fern, Prasad Tadepalli.
9.) Information Theoretical Estimators Toolbox. --Zoltán Szabó.
10.) Off-policy Learning With Eligibility Traces: A Survey. --Matthieu Geist, Bruno Scherrer.
11.) Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule. --Garvesh Raskutti, Martin J. Wainwright, Bin Yu.
12.) Unbiased Generative Semi-Supervised Learning. --Patrick Fox-Roberts, Edward Rosten.
13.) Node-Based Learning of Multiple Gaussian Graphical Models. --Karthik Mohan, Palma London, Maryam Fazel, Daniela Witten, Su-In Lee.
14.) The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R. --Haotian Pang, Han Liu, Robert Vanderbei.
15.) LIBOL: A Library for Online Learning Algorithms. --Steven C.H. Hoi, Jialei Wang, Peilin Zhao.
16.) Improving Markov Network Structure Learning Using Decision Trees. --Daniel Lowd, Jesse Davis.
17.) Ground Metric Learning. --Marco Cuturi, David Avis.
18.) Link Prediction in Graphs with Autoregressive Features. --Emile Richard, Stéphane Gaïffas, Nicolas Vayatis.
19.) Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression. --Francis Bach.
20.) Random Intersection Trees. --Rajen Dinesh Shah, Nicolai Meinshausen.
21.) Reinforcement Learning for Closed-Loop Propofol Anesthesia: A Study in Human Volunteers. --Brett L Moore, Larry D Pyeatt, Vivekanand Kulkarni, Periklis Panousis, Kevin Padrez, Anthony G Doufas.
22.) Clustering Hidden Markov Models with Variational HEM. --Emanuele Coviello, Antoni B. Chan, Gert R.G. Lanckriet.
23.) A Novel M-Estimator for Robust PCA. --Teng Zhang, Gilad Lerman.
24.) Policy Evaluation with Temporal Differences: A Survey and Comparison. --Christoph Dann, Gerhard Neumann, Jan Peters.
25.) Active Learning Using Smooth Relative Regret Approximations with Applications. --Nir Ailon, Ron Begleiter, Esther Ezra; 15(Mar).
26.) An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation. --Henning Sprekeler, Tiziano Zito, Laurenz Wiskott.
27.) Natural Evolution Strategies. --Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, Jürgen Schmidhuber.
28.) Conditional Random Field with High-order Dependencies for Sequence Labeling and Segmentation. --Nguyen Viet Cuong, Nan Ye, Wee Sun Lee, Hai Leong Chieu.
29.) Ellipsoidal Rounding for Nonnegative Matrix Factorization Under Noisy Separability. --Tomohiko Mizutani.
30.) Improving Prediction from Dirichlet Process Mixtures via Enrichment. --Sara Wade, David B. Dunson, Sonia Petrone, Lorenzo Trippa.
31.) Gibbs Max-margin Topic Models with Data Augmentation. --Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang.
32.) A Reliable Effective Terascale Linear Learning System. --Alekh Agarwal, Oliveier Chapelle, Miroslav Dudík, John Langford.
33.) New Learning Methods for Supervised and Unsupervised Preference Aggregation. --Maksims N. Volkovs, Richard S. Zemel.
34.) Prediction and Clustering in Signed Networks: A Local to Global Perspective. --Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari.
35.) Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders. --Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Perez-Cruz.
36.) Robust Near-Separable Nonnegative Matrix Factorization Using Linear Optimization. --Nicolas Gillis, Robert Luce.
37.) Follow the Leader If You Can, Hedge If You Must. --Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen.
38.) Structured Prediction via Output Space Search. --Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli.
39.) Fully Simplified Multivariate Normal Updates in Non-Conjugate Variational Message Passing. --Matt P. Wand.
40.) Towards Ultrahigh Dimensional Feature Selection for Big Data. --Mingkui Tan, Ivor W. Tsang, Li Wang.
41.) Adaptive Sampling for Large Scale Boosting. --Charles Dubout, Francois Fleuret.
42.) Manopt, a Matlab Toolbox for Optimization on Manifolds. --Nicolas Boumal, Bamdev Mishra, P.-A. Absil, Rodolphe Sepulchre.
43.) Training Highly Multiclass Classifiers. --Maya R. Gupta, Samy Bengio, Jason Weston.
44.) Locally Adaptive Factor Processes for Multivariate Time Series. --Daniele Durante, Bruno Scarpa, David B. Dunson.
45.) Iteration Complexity of Feasible Descent Methods for Convex Optimization. --Po-Wei Wang, Chih-Jen Lin.
46.) High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models. --Majid Janzamin, Animashree Anandkumar.
47.) The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo. --Matthew D. Hoffman, Andrew Gelman.
48.) Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife. --Stefan Wager, Trevor Hastie, Bradley Efron.
49.) Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses. --Shivani Agarwal.
50.) Adaptive Minimax Regression Estimation over Sparse ℓq-Hulls. --Zhan Wang, Sandra Paterlini, Fuchang Gao, Yuhong Yang.
2.) Fast SVM Training Using Approximate Extreme Points. --Manu Nandan, Pramod P. Khargonekar, Sachin S. Talathi.
3.) Detecting Click Fraud in Online Advertising: A Data Mining Approach. --Richard Oentaryo, Ee-Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Minh Nhut Nguyen, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar.
4.) EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines. --Marc Claesen, Frank De Smet, Johan A.K. Suykens, Bart De Moor.
5.) A Junction Tree Framework for Undirected Graphical Model Selection. --Divyanshu Vats, Robert D. Nowak.
6.) Axioms for Graph Clustering Quality Functions. --Twan van Laarhoven, Elena Marchiori.
7.) Convex vs Non-Convex Estimators for Regression and Sparse Estimation: the Mean Squared Error Properties of ARD and GLasso. --Aleksandr Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto.
8.) Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning. --Aaron Wilson, Alan Fern, Prasad Tadepalli.
9.) Information Theoretical Estimators Toolbox. --Zoltán Szabó.
10.) Off-policy Learning With Eligibility Traces: A Survey. --Matthieu Geist, Bruno Scherrer.
11.) Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule. --Garvesh Raskutti, Martin J. Wainwright, Bin Yu.
12.) Unbiased Generative Semi-Supervised Learning. --Patrick Fox-Roberts, Edward Rosten.
13.) Node-Based Learning of Multiple Gaussian Graphical Models. --Karthik Mohan, Palma London, Maryam Fazel, Daniela Witten, Su-In Lee.
14.) The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R. --Haotian Pang, Han Liu, Robert Vanderbei.
15.) LIBOL: A Library for Online Learning Algorithms. --Steven C.H. Hoi, Jialei Wang, Peilin Zhao.
16.) Improving Markov Network Structure Learning Using Decision Trees. --Daniel Lowd, Jesse Davis.
17.) Ground Metric Learning. --Marco Cuturi, David Avis.
18.) Link Prediction in Graphs with Autoregressive Features. --Emile Richard, Stéphane Gaïffas, Nicolas Vayatis.
19.) Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression. --Francis Bach.
20.) Random Intersection Trees. --Rajen Dinesh Shah, Nicolai Meinshausen.
21.) Reinforcement Learning for Closed-Loop Propofol Anesthesia: A Study in Human Volunteers. --Brett L Moore, Larry D Pyeatt, Vivekanand Kulkarni, Periklis Panousis, Kevin Padrez, Anthony G Doufas.
22.) Clustering Hidden Markov Models with Variational HEM. --Emanuele Coviello, Antoni B. Chan, Gert R.G. Lanckriet.
23.) A Novel M-Estimator for Robust PCA. --Teng Zhang, Gilad Lerman.
24.) Policy Evaluation with Temporal Differences: A Survey and Comparison. --Christoph Dann, Gerhard Neumann, Jan Peters.
25.) Active Learning Using Smooth Relative Regret Approximations with Applications. --Nir Ailon, Ron Begleiter, Esther Ezra; 15(Mar).
26.) An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation. --Henning Sprekeler, Tiziano Zito, Laurenz Wiskott.
27.) Natural Evolution Strategies. --Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, Jürgen Schmidhuber.
28.) Conditional Random Field with High-order Dependencies for Sequence Labeling and Segmentation. --Nguyen Viet Cuong, Nan Ye, Wee Sun Lee, Hai Leong Chieu.
29.) Ellipsoidal Rounding for Nonnegative Matrix Factorization Under Noisy Separability. --Tomohiko Mizutani.
30.) Improving Prediction from Dirichlet Process Mixtures via Enrichment. --Sara Wade, David B. Dunson, Sonia Petrone, Lorenzo Trippa.
31.) Gibbs Max-margin Topic Models with Data Augmentation. --Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang.
32.) A Reliable Effective Terascale Linear Learning System. --Alekh Agarwal, Oliveier Chapelle, Miroslav Dudík, John Langford.
33.) New Learning Methods for Supervised and Unsupervised Preference Aggregation. --Maksims N. Volkovs, Richard S. Zemel.
34.) Prediction and Clustering in Signed Networks: A Local to Global Perspective. --Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari.
35.) Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders. --Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Perez-Cruz.
36.) Robust Near-Separable Nonnegative Matrix Factorization Using Linear Optimization. --Nicolas Gillis, Robert Luce.
37.) Follow the Leader If You Can, Hedge If You Must. --Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen.
38.) Structured Prediction via Output Space Search. --Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli.
39.) Fully Simplified Multivariate Normal Updates in Non-Conjugate Variational Message Passing. --Matt P. Wand.
40.) Towards Ultrahigh Dimensional Feature Selection for Big Data. --Mingkui Tan, Ivor W. Tsang, Li Wang.
41.) Adaptive Sampling for Large Scale Boosting. --Charles Dubout, Francois Fleuret.
42.) Manopt, a Matlab Toolbox for Optimization on Manifolds. --Nicolas Boumal, Bamdev Mishra, P.-A. Absil, Rodolphe Sepulchre.
43.) Training Highly Multiclass Classifiers. --Maya R. Gupta, Samy Bengio, Jason Weston.
44.) Locally Adaptive Factor Processes for Multivariate Time Series. --Daniele Durante, Bruno Scarpa, David B. Dunson.
45.) Iteration Complexity of Feasible Descent Methods for Convex Optimization. --Po-Wei Wang, Chih-Jen Lin.
46.) High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models. --Majid Janzamin, Animashree Anandkumar.
47.) The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo. --Matthew D. Hoffman, Andrew Gelman.
48.) Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife. --Stefan Wager, Trevor Hastie, Bradley Efron.
49.) Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses. --Shivani Agarwal.
50.) Adaptive Minimax Regression Estimation over Sparse ℓq-Hulls. --Zhan Wang, Sandra Paterlini, Fuchang Gao, Yuhong Yang.
Doppa, Janardhan Rao - Personal Name
Dubout, Charles - Personal Name
Tan, Mingkui - Personal Name
Wand, Matt P. - Personal Name
Rooij, Steven de - Personal Name
Gillis, Nicolas - Personal Name
Ruiz, Francisco J. R. - Personal Name
Volkovs, Maksims N. - Personal Name
Wade, Sara - Personal Name
Boumal, Nicolas - Personal Name
Gupta, Maya R. - Personal Name
Lan, Andrew S. - Personal Name
Srivastava, Nitish - Personal Name
Luxburg, Ulrike von - Personal Name
Kolar, Mladen - Personal Name
Wager, Stefan - Personal Name
Hoffman, Matthew D. - Personal Name
Janzamin, Majid - Personal Name
Durante, Daniele - Personal Name
Mizutani, Tomohiko - Personal Name
Cuong, Nguyen Viet - Personal Name
Geist, Matthieu - Personal Name
Wilson, Aaron - Personal Name
Aravkin, Aleksandr - Personal Name
Laarhoven, Twan van - Personal Name
Vats, Divyanshu - Personal Name
Claesen, Marc - Personal Name
Nandan, Manu - Personal Name
Lowd, Daniel - Personal Name
Raskutti, Garvesh - Personal Name
Mohan, Karthik - Personal Name
Wierstra, Daan - Personal Name
Sprekeler, Henning - Personal Name
Ailon, Nir - Personal Name
Dann, Christoph - Personal Name
Coviello, Emanuele - Personal Name
Shah, Rajen Dinesh - Personal Name
Richard, Emile - Personal Name
Pang, Haotian - Personal Name
Peters, Jonas - Personal Name
Dubout, Charles - Personal Name
Tan, Mingkui - Personal Name
Wand, Matt P. - Personal Name
Rooij, Steven de - Personal Name
Gillis, Nicolas - Personal Name
Ruiz, Francisco J. R. - Personal Name
Volkovs, Maksims N. - Personal Name
Wade, Sara - Personal Name
Boumal, Nicolas - Personal Name
Gupta, Maya R. - Personal Name
Lan, Andrew S. - Personal Name
Srivastava, Nitish - Personal Name
Luxburg, Ulrike von - Personal Name
Kolar, Mladen - Personal Name
Wager, Stefan - Personal Name
Hoffman, Matthew D. - Personal Name
Janzamin, Majid - Personal Name
Durante, Daniele - Personal Name
Mizutani, Tomohiko - Personal Name
Cuong, Nguyen Viet - Personal Name
Geist, Matthieu - Personal Name
Wilson, Aaron - Personal Name
Aravkin, Aleksandr - Personal Name
Laarhoven, Twan van - Personal Name
Vats, Divyanshu - Personal Name
Claesen, Marc - Personal Name
Nandan, Manu - Personal Name
Lowd, Daniel - Personal Name
Raskutti, Garvesh - Personal Name
Mohan, Karthik - Personal Name
Wierstra, Daan - Personal Name
Sprekeler, Henning - Personal Name
Ailon, Nir - Personal Name
Dann, Christoph - Personal Name
Coviello, Emanuele - Personal Name
Shah, Rajen Dinesh - Personal Name
Richard, Emile - Personal Name
Pang, Haotian - Personal Name
Peters, Jonas - Personal Name
Vol. 15 Tahun 2014
1533-7928
e-Journal TI
Inggris
JMLR Inc. - Microtome Publishing
2014
USA
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