Andrey Zhmoginov

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 29

Top Topics

Delta Bar Delta

Convolutional Neural Networks

Knowledge Transfer

Top Venues

Publications

Max Vladymyrov, Andrey Zhmoginov, Mark Sandler
Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learning. Trans. Mach. Learn. Res. 2024 (2024)
Andrey Zhmoginov, Mark Sandler, Nolan Miller, Gus Kristiansen, Max Vladymyrov
Decentralized Learning with Multi-Headed Distillation. CVPR (2023)
Mark Sandler, Andrey Zhmoginov, Max Vladymyrov, Nolan Miller
Training trajectories, mini-batch losses and the curious role of the learning rate. CoRR (2023)
Max Vladymyrov, Andrey Zhmoginov, Mark Sandler
Continual Few-Shot Learning Using HyperTransformers. CoRR (2023)
Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, João Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, Max Vladymyrov
Transformers Learn In-Context by Gradient Descent. ICML (2023)
Andrey Zhmoginov, Mark Sandler, Nolan Miller, Gus Kristiansen, Max Vladymyrov
Decentralized Learning with Multi-Headed Distillation. CoRR (2022)
Mark Sandler, Andrey Zhmoginov, Max Vladymyrov, Andrew Jackson
Fine-tuning Image Transformers using Learnable Memory. CoRR (2022)
Andrey Zhmoginov, Mark Sandler, Maksym Vladymyrov
HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning. ICML (2022)
Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, João Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, Max Vladymyrov
Transformers learn in-context by gradient descent. CoRR (2022)
Andrey Zhmoginov, Mark Sandler, Max Vladymyrov
HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning. CoRR (2022)
Mark Sandler, Andrey Zhmoginov, Max Vladymyrov, Andrew Jackson
Fine-tuning Image Transformers using Learnable Memory. CVPR (2022)
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas
Meta-Learning Bidirectional Update Rules. ICML (2021)
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Andrew Jackson, Tom Madams, Blaise Agüera y Arcas
Meta-Learning Bidirectional Update Rules. CoRR (2021)
Andrey Zhmoginov, Dina Bashkirova, Mark Sandler
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks. CoRR (2021)
Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov, Andrew G. Howard, Brendan Jou, Yukun Zhu, Li Zhang, Rebecca Hwa, Adriana Kovashka
BasisNet: Two-stage Model Synthesis for Efficient Inference. CoRR (2021)
Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov, Andrew Howard, Brendan Jou, Yukun Zhu, Li Zhang, Rebecca Hwa, Adriana Kovashka
BasisNet: Two-Stage Model Synthesis for Efficient Inference. CVPR Workshops (2021)
Andrey Zhmoginov, Ian Fischer, Mark Sandler
Information-Bottleneck Approach to Salient Region Discovery. ECML/PKDD (3) (2020)
Mark Sandler, Andrey Zhmoginov, Liangcheng Luo, Alexander Mordvintsev, Ettore Randazzo, Blaise Agüera y Arcas
Image segmentation via Cellular Automata. CoRR (2020)
Liangchen Luo, Mark Sandler, Zi Lin, Andrey Zhmoginov, Andrew Howard
Large-Scale Generative Data-Free Distillation. CoRR (2020)
Mark Sandler, Jonathan Baccash, Andrey Zhmoginov, Andrew Howard
Non-discriminative data or weak model? On the relative importance of data and model resolution. CoRR (2019)
Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning. ICLR (Poster) (2019)
Andrey Zhmoginov, Ian Fischer, Mark Sandler
Information-Bottleneck Approach to Salient Region Discovery. CoRR (2019)
Mark Sandler, Jonathan Baccash, Andrey Zhmoginov, Andrew Howard
Non-Discriminative Data or Weak Model? On the Relative Importance of Data and Model Resolution. ICCV Workshops (2019)
Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
MobileNetV2: Inverted Residuals and Linear Bottlenecks. CVPR (2018)
Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation. CoRR (2018)
Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard
K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning. CoRR (2018)
Casey Chu, Andrey Zhmoginov, Mark Sandler
CycleGAN, a Master of Steganography. CoRR (2017)
Soravit Changpinyo, Mark Sandler, Andrey Zhmoginov
The Power of Sparsity in Convolutional Neural Networks. CoRR (2017)
Andrey Zhmoginov, Mark Sandler
Inverting face embeddings with convolutional neural networks. CoRR (2016)