10 citations · 12 across the 10 of their papers we have counts for
13 papers
Multi-step domain adaptation by adversarial attack to -divergence
Arip Asadulaev, Alexander Panfilov, Andrey Filchenkov
Adversarial examples are transferable between different models. In our paper, we propose to use this property for multi-step domain adaptation. In unsupervised domain adaptation se…
Easy Batch Normalization
Arip Asadulaev, Alexander Panfilov, Andrey Filchenkov
It was shown that adversarial examples improve object recognition. But what about their opposite side, easy examples? Easy examples are samples that the machine learning model clas…
Connecting adversarial attacks and optimal transport for domain adaptation
Arip Asadulaev, Vitaly Shutov, Alexander Korotin +2
We present a novel algorithm for domain adaptation using optimal transport. In domain adaptation, the goal is to adapt a classifier trained on the source domain samples to the targ…
Towards Robust Object Detection: Bayesian RetinaNet for Homoscedastic Aleatoric Uncertainty Modeling
Natalia Khanzhina, Alexey Lapenok, Andrey Filchenkov
According to recent studies, commonly used computer vision datasets contain about 4% of label errors. For example, the COCO dataset is known for its high level of noise in data lab…
Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling
Qi Yang, Aleksandr Farseev, Andrey Filchenkov
Human personality traits are the key drivers behind our decision-making, influencing our life path on a daily basis. Inference of personality traits, such as Myers-Briggs Personali…
Solving Continuous Control with Episodic Memory
Igor Kuznetsov, Andrey Filchenkov
Episodic memory lets reinforcement learning algorithms remember and exploit promising experience from the past to improve agent performance. Previous works on memory mechanisms sho…