Publication
Implementation and Performance of Pipes in the V-System
Publications associées (39)
End-to-end kernel learning via generative random Fourier features
Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...
ELSEVIER SCI LTD2023ACTOR: Action-Guided Kernel Fuzzing
Fuzzing reliably and efficiently finds bugs in software, including operating system kernels. In general, higher code coverage leads to the discovery of more bugs. This is why most existing kernel fuzzers adopt strategies to generate a series of inputs that ...
Berkeley2023Midas: Systematic Kernel TOCTTOU Protection
Mathias Josef Payer, Atri Bhattacharyya, Uros Tesic
Double-fetch bugs are a plague across all major operating system kernels. They occur when data is fetched twice across the user/kernel trust boundary while allowing concurrent modification. Such bugs enable an attacker to illegally access memory, cause den ...
2022Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data
Matthieu Wyart, Umberto Maria Tomasini, Antonio Sclocchi
Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a 'spectral bias': decomposing the true function f* on the eigenbasis of the ...
JMLR-JOURNAL MACHINE LEARNING RESEARCH2022NrOS: Effective Replication and Sharing in an Operating System
Sanidhya Kashyap, Ankit Bhardwaj
Writing a correct operating system kernel is notoriously hard. Kernel code requires manual memory management and type-unsafe code and must efficiently handle complex, asynchronous events. In addition, increasing CPU core counts further complicate kernel de ...
USENIX ASSOC2021Multikernel Regression with Sparsity Constraint
Michaël Unser, Shayan Aziznejad
In this paper, we provide a Banach-space formulation of supervised learning with generalized total-variation (gTV) regularization. We identify the class of kernel functions that are admissible in this framework. Then, we propose a variation of supervised l ...
2021A conformal dispersion relation: correlations from absorption
We introduce the analog of Kramers-Kronig dispersion relations for correlators of four scalar operators in an arbitrary conformal field theory. The correlator is expressed as an integral over its "absorptive part", defined as a double discontinuity, times ...
2020USBFuzz: A Framework for Fuzzing USB Drivers by Device Emulation
The Universal Serial Bus (USB) connects external devices to a host. This interface exposes the OS kernels and device drivers to attacks by malicious devices. Unfortunately, kernels and drivers were developed under a security model that implicitly trusts co ...
USENIX ASSOC2020Kernel Density Estimation through Density Constrained Near Neighbor Search
In this paper we revisit the kernel density estimation problem: given a kernel K(x, y) and a dataset of n points in high dimensional Euclidean space, prepare a data structure that can quickly output, given a query q, a (1 + epsilon)-approximation to mu := ...
IEEE2020DATASHARENETWORK A Decentralized Privacy-Preserving Search Engine for Investigative Journalists
Carmela González Troncoso, Wouter Lueks, Laurent Girod, Bruno Thomas
Investigative journalists collect large numbers of digital documents during their investigations. These documents can greatly benefit other journalists' work. However, many of these documents contain sensitive information. Hence, possessing such documents ...
USENIX ASSOC2020