Statistical Learning
Representation Learning via Consistent Assignment of Views over Random Partitions
CARP learns prototypes in an end-to-end online fashion using gradient descent without additional non-differentiable modules to solve the cluster assignment problem. CARP optimizes a new pretext task based on random partitions of prototypes that regularizes the model and enforces consistency between views' assignments.
Robust and Actively Secure Serverless Collaborative Learning Olive Franzese
In this work, we propose a peer-to-peer (P2P) learning scheme that is secure against malicious servers and robust to malicious clients.
Achieving O (ฯต 1. 5) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
This class of bilevel problems has been studied extensively from the theoretical perspective in recent years.
Fully Dynamic Consistent Facility Location
Vincent Cohen-Addad, Niklas Oskar D. Hjuler, Nikos Parotsidis, David Saulpic, Chris Schwiegelshohn
Neural Information Processing Systems http://nips.cc/
Replicable Clustering
This means that the algorithm designer needs to balance several conflicting desiderata.
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
Tianyi Chen, Georgios Giannakis, Tao Sun, Wotao Yin
Neural Information Processing Systems http://nips.cc/