... Machine Learning to the rescue . 2019 International Conference on Computing , Communication , and Intelligent ... Efficiently Stealing your Machine Learning Models . doi : 10.1145 / 3338498.3358646 Ren , J. , Zhang , Y. , Zhang ...
... models,” in Proceedings on Privacy Enhancing Technologies, Stockholm, Sweden, July 2019, 2019, 232–249 Hitaj, D ... Efficiently stealing your machine learning models,” in Proceedings of the 18th ACM workshop on privacy in the ...
... The Workshops of the the ThirtySecond AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, 2–7 February 2018, pp. 268–276 (2018) 28. Reith, R.N., Schneider, T., Tkachenko, O.: Efficiently stealing your machine learning ...
This is a step-by-step guide to hyperparameter optimization, starting with what hyperparameters are and how they affect different aspects of machine learning models.
The authors describe how to secure the weights of frontier artificial intelligence and machine learning models (that is, models that match or exceed the capabilities of the most advanced models at the time of their development).
... Efficiently stealing your machine learn- ing models . In : Cavallaro , L. , Kinder , J. , Domingo - Ferrer , J ... Learning , ICML 2020 , 13–18 July 2020 , Virtual Event . Proceedings of Machine Learning Research , vol . 119 , pp ...
You will also find this book useful if you’re an intermediate machine learning developer or data scientist looking for a quick, handy reference to all the concepts of machine learning.
This book explores machine learning (ML) defenses against the many cyberattacks that make our workplaces, schools, private residences, and critical infrastructures vulnerable as a consequence of the dramatic increase in botnets, data ransom ...
The past decade has witnessed the fast growth and tremendous success of machine learning.
While this is incredibly exciting has led to amazing discoveries, it has also exposed challenges and vulnerabilities that simply did not exist, or were not relevant, until now.