A BACKDOOR ATTACK AGAINST LSTM-BASED TEXT CLASSIFICATION SYSTEMS

With the widespread use of deep learning system in many applications, the adversary has strong incentive to explore vulnerabilities of deep neural networks and manipulate them.Backdoor attacks against deep neural networks have been reported to be a new type of threat.In this attack, the adversary will inject backdoors into the model and then cause

When comparing the performance of multi-armed bandit algorithms, the potential impact of missing data is often overlooked.In practice, it also affects their implementation where the simplest approach to overcome this is to continue to sample according to the original bandit algorithm, ignoring missing outcomes.We investigate the impact on performan