Publications associées à Euclidean distance

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Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Yulun Jiang, Chen Liu, Zhuoyi Huang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023

Euclidean distance

Graph Chatbot

Chattez avec Graph Search

Geometric Learning: Leveraging differential geometry for learning and control

Anomalous and Chern topological waves in hyperbolic networks

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

Some Mordell-Weil lattices and applications to sphere packings

Migration distance from birthplace and its association with relative income and employment share among heterosexual couples in Switzerland

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

A structured prediction approach for robot imitation learning

Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Localizing Unsynchronized Sensors With Unknown Sources

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

Migration distance from birthplace and its association with relative income and employment share among heterosexual couples in Switzerland

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Some Mordell-Weil lattices and applications to sphere packings

Geometric Learning: Leveraging differential geometry for learning and control

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

Anomalous and Chern topological waves in hyperbolic networks

Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks

Localizing Unsynchronized Sensors With Unknown Sources

A structured prediction approach for robot imitation learning