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Open High-Resolution Satellite Imagery: The WorldStrat Dataset - With Application to Super-Resolution Julien Cornebise University College London & Why How Ltd j.cornebise@ucl.ac.uk Ivan Orลกoli c
The largest and most varied such publicly available dataset, at Airbus SPOT 6/7 satellites' high resolution of up to 1.5 m/pixel, empowered by European Space Agency's (ESA) Phi-Lab as part of the ESA-funded
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization
Matrix square roots and their inverses arise frequently in machine learning, e.g.,
Learning from Label Proportions: A Mutual Contamination Framework
LLP, prove generalization error bounds associated to two bag generation models, and establish universal consistency with respect to the balanced error rate (BER).
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This state-of-affairs is often justified by the fact that our analysis of the algorithm is often pessimistic.
Toward Efficient Robust Training against Union of โ p Threat Models
MSD) that also uses multi-step ( k = 50) adversarial attacks to generate adversaries for training. However, these methods, owing to their requirement of great number of adversarial training steps as compared to a regular setting for multi-step adversarial training procedure (10 steps), are computationally inefficient.
