… and the projective ranking method. We aim to learn a powerful attack strategy then adapt it
… In our method, based on mutual information, we rank and assess the attack benefits of each …

In cryptography, a side-channel attack is any attack based on … the way to the adoption of
machine learning techniques, ie, … This paper explores the use of machine learning techniques …

… Our attack can be seen as a typical case of universal attacks in IR, ie, a single document …
Reinforcement learning. Reinforcement learning (RL) [50] is a widely used machine learning …

… rankings, one needs to design an appropriate weighted function and train the machine learning
… type of attack are random attack, average attack, bandwagon attack, reverse bandwagon …

… We selected a series of traditional machine learning models for comparative experiments,
and the detailed comparison is shown in Table 5. We concluded that pairwise-based XgB-LtR …

… attack top-k multi-label learning-based image annotation systems (TkML-AP). Our methods
explicitly consider the top-k ranking … proposed as a new learning objective for improving the …

… results, our machine learning approach is successful in detecting combined attacks against
two … For this, we considered combined attacks such as Rank and Version Attack, Rank and …

… attack method named projective ranking to overcome the above limitations. Our idea is to
learn a powerful attack … and rank them accordingly, so the learned attack strategy has better …

As machine learning becomes widely used for automated decisions, attackers have … machine
learning algorithms. In this paper, we perform the first systematic study of poisoning attacks …

… In our experiments, we tried a low-rank approximation based method to detect noise and
AttriGuard is still effective against the method. However, we acknowledge that this does not …