Works matching IS 15324435 AND DT 2017 AND VI 18 AND IP 64-98

Results: 34

Angle-based Multicategory Distance-weighted SVM.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Hui Sun;
Craig, Bruce A.;
Lingsong Zhang

Publication type:

Article

Hierarchical Clustering via Spreading Metrics.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Roy, Aurko;
Pokutta, Sebastian

Publication type:

Article

The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Oliehoek, Frans A.;
Spaan, Matthijs T. J.;
Terwijn, Bas;
Robbel, Philipp;
Messias, João V.

Publication type:

Article

Fisher Consistency for Prior Probability Shift.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Tasche, Dirk

Publication type:

Article

openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Schmitt, Maximilian;
Schuller, Björn

Publication type:

Article

Rank Determination for Low-Rank Data Completion.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Ashraphijuo, Morteza;
Xiaodong Wang;
Aggarwal, Vaneet

Publication type:

Article

Minimax Estimation of Kernel Mean Embeddings.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Tolstikhin, Ilya;
Sriperumbudur, Bharath K.;
Muandety, Krikamol

Publication type:

Article

The Impact of Random Models on Clustering Similarity.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Gates, Alexander J.;
Yong-Yeol Ahn

Publication type:

Article

Optimal Rates for Multi-pass Stochastic Gradient Methods.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Junhong Lin;
Rosasco, Lorenzo

Publication type:

Article

Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Benavoliy, Alessio;
Coraniy, Giorgio;
Demšar, Janez;
Zaffalon, Marco

Publication type:

Article

An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Weiwei Liu;
Tsang, Ivor W.;
Müller, Klaus-Robert

Publication type:

Article

Relational Reinforcement Learning for Planning with Exogenous Effects.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Martínez, David;
Alenyà, Guillem;
Ribeiro, Tony;
Katsumi Inoue;
Torras, Carme

Publication type:

Article

Robust Discriminative Clustering with Sparse Regularizers.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Flammarion, Nicolas;
Palaniappan, Balamurugan;
Bach, Francis

Publication type:

Article

Bayesian Tensor Regression.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Guhaniyogi, Rajarshi;
Qamar, Shaan;
Dunson, David B.

Publication type:

Article

Tests of Mutual or Serial Independence of Random Vectors with Applications.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Bilodeau, Martin;
Nangue, Aurélien Guetsop

Publication type:

Article

Convolutional Neural Networks Analyzed via Convolutional Sparse Coding.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Papyan, Vardan;
Romano, Yaniv;
Elad, Michael

Publication type:

Article

A Bayesian Framework for Learning Rule Sets for Interpretable Classification.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Tong Wang;
Rudin, Cynthia;
Doshi-Velez, Finale;
Yimin Liu;
Klampfl, Erica;
MacNeille, Perry

Publication type:

Article

Multiscale Strategies for Computing Optimal Transport.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Gerber, Samuel;
Maggioni, Mauro

Publication type:

Article

Learning Scalable Deep Kernels with Recurrent Structure.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Al-Shedivat, Maruan;
Wilson, Andrew Gordon;
Saatchi, Yunus;
Zhiting Hu;
Xing, Eric P.

Publication type:

Article

Non-parametric Policy Search with Limited Information Loss.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

van Hoof, Herke;
Neumann, Gerhard;
Peters, Jan

Publication type:

Article

A Robust-Equitable Measure for Feature Ranking and Selection.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Ding, A. Adam;
Dy, Jennifer G.;
Yi Li;
Yale Chang

Publication type:

Article

Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Yuchen Zhang;
Lin Xiao

Publication type:

Article

Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Weiwei Liu;
Tsang, Ivor W.

Publication type:

Article

Quantifying the Informativeness of Similarity Measurements.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Brockmeier, Austin J.;
Tingting Mu;
Ananiadou, Sophia;
Goulermas, John Y.

Publication type:

Article

Recovering PCA and Sparse PCA via Hybrid-(ℓ1; ℓ2) Sparse Sampling of Data Elements.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Kundu, Abhisek;
Drineas, Petros;
Magdon-Ismail, Malik

Publication type:

Article

Distributed Learning with Regularized Least Squares.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Shao-Bo Lin;
Xin Guo;
Ding-Xuan Zhou

Publication type:

Article

Identifying Unreliable and Adversarial Workers in Crowdsourced Labeling Tasks.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Jagabathula, Srikanth;
Subramanian, Lakshminarayanan;
Venkataraman, Ashwin

Publication type:

Article

Soft Margin Support Vector Classiffcation as Buffered Probability Minimization.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Norton, Matthew;
Mafusalov, Alexander;
Uryasev, Stan

Publication type:

Article

Hierarchically Compositional Kernels for Scalable Nonparametric Learning.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Jie Chen;
Avron, Haim;
Sindhwani, Vikas

Publication type:

Article

Variational Particle Approximations.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Saeedi, Ardavan;
Kulkarni, Tejas D.;
Mansinghka, Vikash K.;
Gershman, Samuel J.

Publication type:

Article

Sharp Oracle Inequalities for Square Root Regularization.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Stucky, Benjamin;
van de Geer, Sara

Publication type:

Article

Learning Partial Policies to Speedup MDP Tree Search via Reduction to I.I.D. Learning.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Pinto, Jervis;
Fern, Alan

Publication type:

Article

Parallel Symmetric Class Expression Learning.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Tran, An C.;
Dietrich, Jens;
Guesgen, Hans W.;
Marsland, Stephen

Publication type:

Article

A distributed block coordinate descent method for training l1 regularized linear classifiers.

Published in:

Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1

By:

Mahajan, Dhruv;
Keerthi, S. Sathiya;
Sundararajan, S.

Publication type:

Article

Works matching IS 15324435 AND DT 2017 AND VI 18 AND IP 64-98

Angle-based Multicategory Distance-weighted SVM.

Hierarchical Clustering via Spreading Metrics.

The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems.

Fisher Consistency for Prior Probability Shift.

openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit.

Rank Determination for Low-Rank Data Completion.

Minimax Estimation of Kernel Mean Embeddings.

The Impact of Random Models on Clustering Similarity.

Optimal Rates for Multi-pass Stochastic Gradient Methods.

Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis.

An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels.

Relational Reinforcement Learning for Planning with Exogenous Effects.

Robust Discriminative Clustering with Sparse Regularizers.

Bayesian Tensor Regression.

Tests of Mutual or Serial Independence of Random Vectors with Applications.

Convolutional Neural Networks Analyzed via Convolutional Sparse Coding.

A Bayesian Framework for Learning Rule Sets for Interpretable Classification.

Multiscale Strategies for Computing Optimal Transport.

Learning Scalable Deep Kernels with Recurrent Structure.

Non-parametric Policy Search with Limited Information Loss.

A Robust-Equitable Measure for Feature Ranking and Selection.

Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization.

Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions.

Quantifying the Informativeness of Similarity Measurements.

Recovering PCA and Sparse PCA via Hybrid-(ℓ<sub>1</sub>; ℓ<sub>2</sub>) Sparse Sampling of Data Elements.

Distributed Learning with Regularized Least Squares.

Identifying Unreliable and Adversarial Workers in Crowdsourced Labeling Tasks.

Soft Margin Support Vector Classiffcation as Buffered Probability Minimization.

Hierarchically Compositional Kernels for Scalable Nonparametric Learning.

Variational Particle Approximations.

Sharp Oracle Inequalities for Square Root Regularization.

Learning Partial Policies to Speedup MDP Tree Search via Reduction to I.I.D. Learning.

Parallel Symmetric Class Expression Learning.

A distributed block coordinate descent method for training l<sub>1</sub> regularized linear classifiers.