Papers
Recurrent Relational Networks
Rasmus Palm, Ulrich Paquet, Ole Winther
Learning To Learn Around A Common Mean
Giulia Denevi, Carlo Ciliberto, Dimitris Stamos et al.
Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples
Guanhong Tao, Shiqing Ma, Yingqi Liu et al.
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
Hardware Conditioned Policies for Multi-Robot Transfer Learning
Tao Chen, Adithyavairavan Murali, Abhinav Gupta
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu, Miltiadis Allamanis, Marc Brockschmidt et al.
Infinite-Horizon Gaussian Processes
Arno Solin, James Hensman, Richard E Turner
On the Local Hessian in Back-propagation
Huishuai Zhang, Wei Chen, Tie-Yan Liu
Porcupine Neural Networks: Approximating Neural Network Landscapes
Soheil Feizi, Hamid Javadi, Jesse Zhang et al.
The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning
Jesse Krijthe, Marco Loog
Latent Alignment and Variational Attention
Yuntian Deng, Yoon Kim, Justin Chiu et al.
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi et al.
Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions
Boris Muzellec, Marco Cuturi
Norm-Ranging LSH for Maximum Inner Product Search
Xiao Yan, Jinfeng Li, Xinyan Dai et al.
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Dominik Linzner, Heinz Koeppl
REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis
Yu-Shao Peng, Kai-Fu Tang, Hsuan-Tien Lin et al.
Probabilistic Matrix Factorization for Automated Machine Learning
Nicolo Fusi, Rishit Sheth, Melih Elibol
Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport
Theo Lacombe, Marco Cuturi, Steve OUDOT
On the Dimensionality of Word Embedding
Zi Yin, Yuanyuan Shen
Nonparametric learning from Bayesian models with randomized objective functions
Simon Lyddon, Stephen Walker, Chris C Holmes
Mental Sampling in Multimodal Representations
Jianqiao Zhu, Adam Sanborn, Nick Chater
Model Agnostic Supervised Local Explanations
Gregory Plumb, Denali Molitor, Ameet S Talwalkar
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property
Yi Zhou, Zhe Wang, Yingbin Liang
Sparsified SGD with Memory
Sebastian U Stich, Jean-Baptiste Cordonnier, Martin Jaggi