Papers
Augmentable Gamma Belief Networks
Mingyuan Zhou, Yulai Cong, Bo Chen
The Teaching Dimension of Linear Learners
Ji Liu, Xiaojin Zhu
Optimal Estimation and Completion of Matrices with Biclustering Structures
Chao Gao, Yu Lu, Zongming Ma et al.
A General Framework for Constrained Bayesian Optimization using Information-based Search
José Miguel Hernández-Lobato, Michael A. Gelbart, Ryan P. Adams et al.
Exploration of the (Non-)Asymptotic Bias and Variance of Stochastic Gradient Langevin Dynamics
Sebastian J. Vollmer, Konstantinos C. Zygalakis, Yee Whye Teh
Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs
Alberto N. Escalante-B., Laurenz Wiskott
Minimum Density Hyperplanes
Nicos G. Pavlidis, David P. Hofmeyr, Sotiris K. Tasoulis
New Perspectives on k-Support and Cluster Norms
Andrew M. McDonald, Massimiliano Pontil, Dimitris Stamos
Importance Weighting Without Importance Weights: An Efficient Algorithm for Combinatorial Semi-Bandits
Gergely Neu, Gábor Bartók
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
Weijie Su, Stephen Boyd, Emmanuel J. Candès
Learning Theory for Distribution Regression
Zoltán Szabó, Bharath K. Sriperumbudur, Barnabás Póczos et al.
A General Framework for Consistency of Principal Component Analysis
Dan Shen, Haipeng Shen, J. S. Marron
Kernel Estimation and Model Combination in A Bandit Problem with Covariates
Wei Qian, Yuhong Yang
Megaman: Scalable Manifold Learning in Python
James McQueen, Marina Meilă, Jacob VanderPlas et al.
Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means
Twan van Laarhoven, Elena Marchiori
Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models
Jiahe Lin, Sumanta Basu, Moulinath Banerjee et al.
True Online Temporal-Difference Learning
Harm van Seijen, A. Rupam Mahmood, Patrick M. Pilarski et al.
MOCCA: Mirrored Convex/Concave Optimization for Nonconvex Composite Functions
Rina Foygel Barber, Emil Y. Sidky
Covariance-based Clustering in Multivariate and Functional Data Analysis
Francesca Ieva, Anna Maria Paganoni, Nicholas Tarabelloni
Large Scale Visual Recognition through Adaptation using Joint Representation and Multiple Instance Learning
Judy Hoffman, Deepak Pathak, Eric Tzeng et al.
Sparse PCA via Covariance Thresholding
Yash Deshpande, Andrea Montanari
Multiscale Adaptive Representation of Signals: I. The Basic Framework
Cheng Tai, Weinan E
Regularized Policy Iteration with Nonparametric Function Spaces
Amir-massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári et al.