Papers
Forward Amortized Inference for Likelihood-Free Variational Marginalization
Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya et al.
Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior
Gaël Letarte, Emilie Morvant, Pascal Germain
A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure
Juho Lee, Lancelot James, Seungjin Choi et al.
Gaussian Process Latent Variable Alignment Learning
Ieva Kazlauskaite, Carl Henrik Ek, Neill Campbell
Nonlinear Acceleration of Primal-Dual Algorithms
Raghu Bollapragada, Damien Scieur, Alexandre d’Aspremont
Bayesian Learning of Neural Network Architectures
Georgi Dikov, Justin Bayer
Classification using margin pursuit
Matthew J. Holland
Robust descent using smoothed multiplicative noise
Matthew J. Holland
Fisher Information and Natural Gradient Learning in Random Deep Networks
Shun-ichi Amari, Ryo Karakida, Masafumi Oizumi
Defending against Whitebox Adversarial Attacks via Randomized Discretization
Yuchen Zhang, Percy Liang
Exploring Fast and Communication-Efficient Algorithms in Large-Scale Distributed Networks
Yue Yu, Jiaxiang Wu, Junzhou Huang
Robust Graph Embedding with Noisy Link Weights
Akifumi Okuno, Hidetoshi Shimodaira
Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability
Akifumi Okuno, Geewook Kim, Hidetoshi Shimodaira
Reversible Jump Probabilistic Programming
David A. Roberts, Marcus Gallagher, Thomas Taimre
Optimal Testing in the Experiment-rich Regime
Sven Schmit, Virag Shah, Ramesh Johari
On Target Shift in Adversarial Domain Adaptation
Yitong Li, Michael Murias, Samantha Major et al.
Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms
Mathieu Blondel, Andre Martins, Vlad Niculae
Temporal Quilting for Survival Analysis
Changhee Lee, William Zame, Ahmed Alaa et al.
Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators
Oren Mangoubi, Aaron Smith
Computation Efficient Coded Linear Transform
Sinong Wang, Jiashang Liu, Ness Shroff et al.
What made you do this? Understanding black-box decisions with sufficient input subsets
Brandon Carter, Jonas Mueller, Siddhartha Jain et al.
On Connecting Stochastic Gradient MCMC and Differential Privacy
Bai Li, Changyou Chen, Hao Liu et al.
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems
Emanuel Laude, Tao Wu, Daniel Cremers