Papers
Parallel Symmetric Class Expression Learning
An C. Tran, Jens Dietrich, Hans W. Guesgen et al.
Fundamental Conditions for Low-CP-Rank Tensor Completion
Morteza Ashraphijuo, Xiaodong Wang
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA
Yannis Papanikolaou, James R. Foulds, Timothy N. Rubin et al.
On the Propagation of Low-Rate Measurement Error to Subgraph Counts in Large Networks
Prakash Balachandran, Eric D. Kolaczyk, Weston D. Viles
Achieving Optimal Misclassification Proportion in Stochastic Block Models
Chao Gao, Zongming Ma, Anderson Y. Zhang et al.
Joint Label Inference in Networks
Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang et al.
Lens Depth Function and k-Relative Neighborhood Graph: Versatile Tools for Ordinal Data Analysis
Matthäus Kleindessner, Ulrike von Luxburg
Density Estimation in Infinite Dimensional Exponential Families
Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton et al.
Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences
Takashi Takenouchi, Takafumi Kanamori
On the Consistency of Ordinal Regression Methods
Fabian Pedregosa, Francis Bach, Alexandre Gramfort
Two New Approaches to Compressed Sensing Exhibiting Both Robust Sparse Recovery and the Grouping Effect
Mehmet Eren Ahsen, Niharika Challapalli, Mathukumalli Vidyasagar
Reconstructing Undirected Graphs from Eigenspaces
Yohann De Castro, Thibault Espinasse, Paul Rochet
Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques
Debarghya Ghoshdastidar, Ambedkar Dukkipati
Clustering from General Pairwise Observations with Applications to Time-varying Graphs
Shiau Hong Lim, Yudong Chen, Huan Xu
Explaining the Success of AdaBoost and Random Forests as Interpolating Classifiers
Abraham J. Wyner, Matthew Olson, Justin Bleich et al.
On Markov chain Monte Carlo methods for tall data
Rémi Bardenet, Arnaud Doucet, Chris Holmes
Distributed Semi-supervised Learning with Kernel Ridge Regression
Xiangyu Chang, Shao-Bo Lin, Ding-Xuan Zhou
Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality
Samory Kpotufe, Nakul Verma
Bayesian Learning of Dynamic Multilayer Networks
Daniele Durante, Nabanita Mukherjee, Rebecca C. Steorts
Learning Local Dependence In Ordered Data
Guo Yu, Jacob Bien
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution
Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez et al.
GPflow: A Gaussian Process Library using TensorFlow
Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson et al.