Papers
Generalized Maximum Entropy Estimation
Tobias Sutter, David Sutter, Peyman Mohajerin Esfahani et al.
Multiclass Boosting: Margins, Codewords, Losses, and Algorithms
Mohammad Saberian, Nuno Vasconcelos
Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis
Nicolás García Trillos, Daniel Sanz-Alonso, Ruiyi Yang
Gaussian Processes with Linear Operator Inequality Constraints
Christian Agrell
Stochastic Variance-Reduced Cubic Regularization Methods
Dongruo Zhou, Pan Xu, Quanquan Gu
Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes
Luca Venturi, Afonso S. Bandeira, Joan Bruna
Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model
Sophie Burkhardt, Stefan Kramer
Logical Explanations for Deep Relational Machines Using Relevance Information
Ashwin Srinivasan, Lovekesh Vig, Michael Bain
Time-to-Event Prediction with Neural Networks and Cox Regression
Håvard Kvamme, Ørnulf Borgan, Ida Scheel
Unsupervised Basis Function Adaptation for Reinforcement Learning
Edward Barker, Charl Ras
Causal Learning via Manifold Regularization
Steven M. Hill, Chris J. Oates, Duncan A. Blythe et al.
Learning Representations of Persistence Barcodes
Christoph D. Hofer, Roland Kwitt, Marc Niethammer
ORCA: A Matlab/Octave Toolbox for Ordinal Regression
Javier Sánchez-Monedero, Pedro A. Gutiérrez, María Pérez-Ortiz
Deep Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Daniel J. Russo et al.
ADMMBO: Bayesian Optimization with Unknown Constraints using ADMM
Setareh Ariafar, Jaume Coll-Font, Dana Brooks et al.
Approximate Profile Maximum Likelihood
Dmitri S. Pavlichin, Jiantao Jiao, Tsachy Weissman
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Bin Hong, Weizhong Zhang, Wei Liu et al.
Ivanov-Regularised Least-Squares Estimators over Large RKHSs and Their Interpolation Spaces
Stephen Page, Steffen Grünewälder
Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models
Kean Ming Tan, Junwei Lu, Tong Zhang et al.
Binarsity: a penalization for one-hot encoded features in linear supervised learning
Mokhtar Z. Alaya, Simon Bussy, Stéphane Gaïffas et al.
Generic Inference in Latent Gaussian Process Models
Edwin V. Bonilla, Karl Krauth, Amir Dezfouli
Graph Reduction with Spectral and Cut Guarantees
Andreas Loukas
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery
Richard Y. Zhang, Somayeh Sojoudi, Javad Lavaei