Papers
The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems
Frans A. Oliehoek, Matthijs T. J. Spaan, Bas Terwijn et al.
Hierarchical Clustering via Spreading Metrics
Aurko Roy, Sebastian Pokutta
The Impact of Random Models on Clustering Similarity
Alexander J. Gates, Yong-Yeol Ahn
Minimax Estimation of Kernel Mean Embeddings
Ilya Tolstikhin, Bharath K. Sriperumbudur, Krikamol Muandet
Angle-based Multicategory Distance-weighted SVM
Hui Sun, Bruce A. Craig, Lingsong Zhang
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
Yuchen Zhang, Lin Xiao
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding
Vardan Papyan, Yaniv Romano, Michael Elad
Learning Scalable Deep Kernels with Recurrent Structure
Maruan Al-Shedivat, Andrew Gordon Wilson, Yunus Saatchi et al.
Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions
Weiwei Liu, Ivor W. Tsang
Robust Discriminative Clustering with Sparse Regularizers
Nicolas Flammarion, Balamurugan Palaniappan, Francis Bach
Bayesian Tensor Regression
Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson
Relational Reinforcement Learning for Planning with Exogenous Effects
David Martínez, Guillem Alenyà, Tony Ribeiro et al.
Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis
Alessio Benavoli, Giorgio Corani, Janez Demšar et al.
Quantifying the Informativeness of Similarity Measurements
Austin J. Brockmeier, Tingting Mu, Sophia Ananiadou et al.
Recovering PCA and Sparse PCA via Hybrid-(l1,l2) Sparse Sampling of Data Elements
Abhisek Kundu, Petros Drineas, Malik Magdon-Ismail
Tests of Mutual or Serial Independence of Random Vectors with Applications
Martin Bilodeau, Aurélien Guetsop Nangue
Non-parametric Policy Search with Limited Information Loss
Herke van Hoof, Gerhard Neumann, Jan Peters
Multiscale Strategies for Computing Optimal Transport
Samuel Gerber, Mauro Maggioni
A Robust-Equitable Measure for Feature Ranking and Selection
A. Adam Ding, Jennifer G. Dy, Yi Li et al.
A Bayesian Framework for Learning Rule Sets for Interpretable Classification
Tong Wang, Cynthia Rudin, Finale Doshi-Velez et al.
Variational Particle Approximations
Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka et al.
Soft Margin Support Vector Classification as Buffered Probability Minimization
Matthew Norton, Alexander Mafusalov, Stan Uryasev
Sharp Oracle Inequalities for Square Root Regularization
Benjamin Stucky, Sara van de Geer
Hierarchically Compositional Kernels for Scalable Nonparametric Learning
Jie Chen, Haim Avron, Vikas Sindhwani
Learning Partial Policies to Speedup MDP Tree Search via Reduction to I.I.D. Learning
Jervis Pinto, Alan Fern