430 citations · 435 across the 3 of their papers we have counts for
6 papers
Decentralized Learning with Multi-Headed Distillation
Andrey Zhmoginov, Mark Sandler, Nolan Miller +2
Decentralized learning with private data is a central problem in machine learning. We propose a novel distillation-based decentralized learning technique that allows multiple agent…
Fine-tuning Image Transformers using Learnable Memory
Mark Sandler, Andrey Zhmoginov, Max Vladymyrov +1
In this paper we propose augmenting Vision Transformer models with learnable memory tokens. Our approach allows the model to adapt to new tasks, using few parameters, while optiona…
Meta-Learning Bidirectional Update Rules
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov +4
In this paper, we introduce a new type of generalized neural network where neurons and synapses maintain multiple states. We show that classical gradient-based backpropagation in n…
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander D'Amour, Katherine Heller, Dan Moldovan +37
ML models often exhibit unexpectedly poor behavior when they are deployed in real-world domains. We identify underspecification as a key reason for these failures. An ML pipeline i…
No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
Max Vladymyrov
Nonlinear embedding manifold learning methods provide invaluable visual insights into the structure of high-dimensional data. However, due to a complicated nonconvex objective func…
NEWS: Nuclear Emulsions for WIMP Search
A. Aleksandrov, A. Anokhina, T. Asada +56
Nowadays there is compelling evidence for the existence of dark matter in the Universe. A general consensus has been expressed on the need for a directional sensitive detector to c…