Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an embedding space. This implies that the utility of such representations is no ...
In many real world medical image classification settings we do not have access to samples of all possible disease classes, while a robust system is expected to give high performance in recognizing novel test data. We propose a generalized zero shot learnin ...
Most of the cryptographic protocols that we use frequently on the internet are designed in a fashion that they are not necessarily suitable to run in constrained environments. Applications that run on limited-battery, with low computational power, or area ...
Spectre, Meltdown, and related attacks have demonstrated that kernels, hypervisors, trusted execution environments, and browsers are prone to information disclosure through micro-architectural weaknesses. However, it remains unclear as to what extent other ...
Trusted Execution Environments (TEEs), such as Intel SGX enclaves, use hardware to ensure the confidentiality and integrity of operations on sensitive data. While the technology is available on many processors, the complexity of its programming model and i ...
A Ka-band transition between a rectangular waveguide and a suspended stripline (SSL) is proposed. It uses a configuration in which the SSL substrate is perpendicular to the waveguide main axis. A patch printed on the SSL substrate is used to match the char ...
We consider several "provably secure" hash functions that compute simple sums in a well chosen group (G,*). Security properties of such functions provably translate in a natural way to computational problems in G that are simple to define and possibly also ...
