Papers
Graphical Time Warping for Joint Alignment of Multiple Curves
Yizhi Wang, David J. Miller, Kira Poskanzer et al.
Adaptive Neural Compilation
Rudy R Bunel, Alban Desmaison, Pawan K Mudigonda et al.
On Explore-Then-Commit strategies
Aurelien Garivier, Tor Lattimore, Emilie Kaufmann
Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated
Namrata Vaswani, Han Guo
Gaussian Processes for Survival Analysis
Tamara Fernandez, Nicolas Rivera, Yee Whye Teh
Disentangling factors of variation in deep representation using adversarial training
Michael F Mathieu, Junbo Jake Zhao, Junbo Zhao et al.
Learning Additive Exponential Family Graphical Models via ℓ_2,1-norm Regularized M-Estimation
Xiaotong Yuan, Ping Li, Tong Zhang et al.
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Tim Salimans, Diederik P. Kingma
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Yunchen Pu, Zhe Gan, Ricardo Henao et al.
Fairness in Learning: Classic and Contextual Bandits
Matthew Joseph, Michael Kearns, Jamie H Morgenstern et al.
Dense Associative Memory for Pattern Recognition
Dmitry Krotov, John J. Hopfield
Optimal Binary Classifier Aggregation for General Losses
Akshay Balsubramani, Yoav S Freund
A Multi-step Inertial Forward-Backward Splitting Method for Non-convex Optimization
Jingwei Liang, Jalal Fadili, Gabriel Peyré
Parameter Learning for Log-supermodular Distributions
Tatiana Shpakova, Francis Bach
Exact Recovery of Hard Thresholding Pursuit
Xiaotong Yuan, Ping Li, Tong Zhang
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision
Xinchen Yan, Jimei Yang, Ersin Yumer et al.
Combinatorial semi-bandit with known covariance
Rémy Degenne, Vianney Perchet
Learning Kernels with Random Features
Aman Sinha, John C. Duchi
Efficient Neural Codes under Metabolic Constraints
Zhuo Wang, Xue-Xin Wei, Alan Stocker et al.
Deep Neural Networks with Inexact Matching for Person Re-Identification
Arulkumar Subramaniam, Moitreya Chatterjee, Anurag Mittal
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much
Bryan D He, Christopher M De Sa, Ioannis Mitliagkas et al.
Unsupervised Learning from Noisy Networks with Applications to Hi-C Data
Bo Wang, Junjie Zhu, Armin Pourshafeie et al.
Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables
Mauro Scanagatta, Giorgio Corani, Cassio P de Campos et al.
Contextual semibandits via supervised learning oracles
Akshay Krishnamurthy, Alekh Agarwal, Miro Dudik
Scaled Least Squares Estimator for GLMs in Large-Scale Problems
Murat A Erdogdu, Lee H Dicker, Mohsen Bayati