Papers
Learning Natural Programs from a Few Examples in Real-Time
Nagarajan Natarajan, Danny Simmons, Naren Datha et al.
Sparse Feature Selection in Kernel Discriminant Analysis via Optimal Scoring
Alexander F. Lapanowski, Irina Gaynanova
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs
Alexander Bauer, Shinichi Nakajima, Nico Goernitz et al.
On Structure Priors for Learning Bayesian Networks
Ralf Eggeling, Jussi Viinikka, Aleksis Vuoksenmaa et al.
Statistical Learning under Nonstationary Mixing Processes
Steve Hanneke, Liu Yang
Finding the bandit in a graph: Sequential search-and-stop
Pierre Perrault, Vianney Perchet, Michal Valko
Semi-supervised clustering for de-duplication
Shrinu Kushagra, Shai Ben-David, Ihab Ilyas
Differentially Private Online Submodular Minimization
Adrian Rivera Cardoso, Rachel Cummings
A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions
Feras A. Saad, Cameron E. Freer, Nathanael L. Ackerman et al.
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning
Guillaume Rabusseau, Tianyu Li, Doina Precup
Inverting Supervised Representations with Autoregressive Neural Density Models
Charlie Nash, Nate Kushman, Christopher K.I. Williams
Does data interpolation contradict statistical optimality?
Mikhail Belkin, Alexander Rakhlin, Alexandre B. Tsybakov
Direct Acceleration of SAGA using Sampled Negative Momentum
Kaiwen Zhou, Qinghua Ding, Fanhua Shang et al.
Top Feasible Arm Identification
Julian Katz-Samuels, Clayton Scott
Adaptive Gaussian Copula ABC
Yanzhi Chen, Michael U. Gutmann
Sample Complexity of Sinkhorn Divergences
Aude Genevay, Lénaïc Chizat, Francis Bach et al.
Stochastic algorithms with descent guarantees for ICA
Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso et al.
Calibrating Deep Convolutional Gaussian Processes
Gia-Lac Tran, Edwin V. Bonilla, John Cunningham et al.
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit
Shengyu Zhu, Biao Chen, Pengfei Yang et al.
Gain estimation of linear dynamical systems using Thompson Sampling
Matias I. Müller, Cristian R. Rojas
Learning One-hidden-layer ReLU Networks via Gradient Descent
Xiao Zhang, Yaodong Yu, Lingxiao Wang et al.
Training a Spiking Neural Network with Equilibrium Propagation
Peter O’Connor, Efstratios Gavves, Max Welling
Fast and Robust Shortest Paths on Manifolds Learned from Data
Georgios Arvanitidis, Soren Hauberg, Philipp Hennig et al.
Nonconvex Matrix Factorization from Rank-One Measurements
Yuanxin Li, Cong Ma, Yuxin Chen et al.
Iterative Bayesian Learning for Crowdsourced Regression
Jungseul Ok, Sewoong Oh, Yunhun Jang et al.