Papers
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals
Emilie Kaufmann, Wouter M. Koolen
mlr3pipelines - Flexible Machine Learning Pipelines in R
Martin Binder, Florian Pfisterer, Michel Lang et al.
Model Linkage Selection for Cooperative Learning
Jiaying Zhou, Jie Ding, Kean Ming Tan et al.
Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions
HanQin Cai, Keaton Hamm, Longxiu Huang et al.
Multi-class Gaussian Process Classification with Noisy Inputs
Carlos Villacampa-Calvo, Bryan Zaldívar, Eduardo C. Garrido-Merchán et al.
Multilevel Monte Carlo Variational Inference
Masahiro Fujisawa, Issei Sato
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis
Andreas Damianou, Neil D. Lawrence, Carl Henrik Ek
MushroomRL: Simplifying Reinforcement Learning Research
Carlo D'Eramo, Davide Tateo, Andrea Bonarini et al.
mvlearn: Multiview Machine Learning in Python
Ronan Perry, Gavin Mischler, Richard Guo et al.
Neighborhood Structure Assisted Non-negative Matrix Factorization and Its Application in Unsupervised Point-wise Anomaly Detection
Imtiaz Ahmed, Xia Ben Hu, Mithun P. Acharya et al.
NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation
Anastasis Kratsios, Cody Hyndman
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks
Henning Petzka, Cristian Sminchisescu
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders
Oskar Allerbo, Rebecka Jörnsten
Nonparametric Continuous Sensor Registration
William Clark, Maani Ghaffari, Anthony Bloch
Nonparametric Modeling of Higher-Order Interactions via Hypergraphons
Krishnakumar Balasubramanian
Non-parametric Quantile Regression via the K-NN Fused Lasso
Steven Siwei Ye, Oscar Hernan Madrid Padilla
Normalizing Flows for Probabilistic Modeling and Inference
George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende et al.
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization
Ali Ramezani-Kebrya, Fartash Faghri, Ilya Markov et al.
Oblivious Data for Fairness with Kernels
Steffen Grünewälder, Azadeh Khaleghi
On ADMM in Deep Learning: Convergence and Saturation-Avoidance
Jinshan Zeng, Shao-Bo Lin, Yuan Yao et al.
On efficient multilevel Clustering via Wasserstein distances
Viet Huynh, Nhat Ho, Nhan Dam et al.
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them
Saber Salehkaleybar, Arsalan Sharifnassab, S. Jamaloddin Golestani
Online stochastic gradient descent on non-convex losses from high-dimensional inference
Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath
On lp-hyperparameter Learning via Bilevel Nonsmooth Optimization
Takayuki Okuno, Akiko Takeda, Akihiro Kawana et al.
On Multi-Armed Bandit Designs for Dose-Finding Trials
Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere