153 citations · 344 across the 11 of their papers we have counts for
14 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…
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks
Andrey Zhmoginov, Dina Bashkirova, Mark Sandler
Conditional computation and modular networks have been recently proposed for multitask learning and other problems as a way to decompose problem solving into multiple reusable comp…
Limit on the Electric Charge of Antihydrogen
A. Capra, C. Amole, M. D. Ashkezari +37
The ALPHA collaboration has successfully demonstrated the production and the confinement of cold antihydrogen, . An analysis of trapping data allowed a strin…
BasisNet: Two-stage Model Synthesis for Efficient Inference
Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov +6
In this work, we present BasisNet which combines recent advancements in efficient neural network architectures, conditional computation, and early termination in a simple new form.…
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…