Papers
Dropout Training, Data-dependent Regularization, and Generalization Bounds
Wenlong Mou, Yuchen Zhou, Jun Gao et al.
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
Marine Le Morvan, Jean-Philippe Vert
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
Thomas Moreau, Laurent Oudre, Nicolas Vayatis
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
Aryan Mokhtari, Hamed Hassani, Amin Karbasi
The Hierarchical Adaptive Forgetting Variational Filter
Vincent Moens
Data Summarization at Scale: A Two-Stage Submodular Approach
Marko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam et al.
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick et al.
Differentiable Abstract Interpretation for Provably Robust Neural Networks
Matthew Mirman, Timon Gehr, Martin Vechev
Training Neural Machines with Trace-Based Supervision
Matthew Mirman, Dimitar Dimitrov, Pavle Djordjevic et al.
Differentiable plasticity: training plastic neural networks with backpropagation
Thomas Miconi, Kenneth Stanley, Jeff Clune
One-Shot Segmentation in Clutter
Claudio Michaelis, Matthias Bethge, Alexander Ecker
On the Implicit Bias of Dropout
Poorya Mianjy, Raman Arora, Rene Vidal
Stochastic PCA with ℓ_2 and ℓ_1 Regularization
Poorya Mianjy, Raman Arora
The Hidden Vulnerability of Distributed Learning in Byzantium
El-Mahdi El-Mhamdi, Rachid Guerraoui, Sébastien Rouault
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back
Elliot Meyerson, Risto Miikkulainen
prDeep: Robust Phase Retrieval with a Flexible Deep Network
Christopher Metzler, Phillip Schniter, Ashok Veeraraghavan et al.
Configurable Markov Decision Processes
Alberto Maria Metelli, Mirco Mutti, Marcello Restelli
Which Training Methods for GANs do actually Converge?
Lars Mescheder, Andreas Geiger, Sebastian Nowozin
Ranking Distributions based on Noisy Sorting
Adil El Mesaoudi-Paul, Eyke Hüllermeier, Robert Busa-Fekete
Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch, Mathieu Blondel
Bounds on the Approximation Power of Feedforward Neural Networks
Mohammad Mehrabi, Aslan Tchamkerten, MANSOOR YOUSEFI
Optimization, fast and slow: optimally switching between local and Bayesian optimization
Mark McLeod, Stephen Roberts, Michael A. Osborne
Bayesian Model Selection for Change Point Detection and Clustering
Othmane Mazhar, Cristian Rojas, Carlo Fischione et al.
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin, Andreas Loukas, Pierre Vandergheynst
Streaming Principal Component Analysis in Noisy Setting
Teodor Vanislavov Marinov, Poorya Mianjy, Raman Arora