Zobrazeno 1 - 10
of 2 712
pro vyhledávání: '"Stemmer P"'
Publikováno v:
Physical Review X 14, 041037 (2024)
The quantum Wigner crystal is a many-body state where Coulombic repulsion quenches the kinetic energy of electrons, causing them to crystallize into a lattice. Experimental realization of a quantum Wigner crystal at zero magnetic field has been a lon
Externí odkaz:
http://arxiv.org/abs/2411.07230
Cardinality sketches are compact data structures for representing sets or vectors, enabling efficient approximation of their cardinality (or the number of nonzero entries). These sketches are space-efficient, typically requiring only logarithmic stor
Externí odkaz:
http://arxiv.org/abs/2411.06370
We introduce efficient differentially private (DP) algorithms for several linear algebraic tasks, including solving linear equalities over arbitrary fields, linear inequalities over the reals, and computing affine spans and convex hulls. As an applic
Externí odkaz:
http://arxiv.org/abs/2411.03087
Autor:
Stemmer, Georg, Lopez, Jose A., Ontiveros, Juan A. Del Hoyo, Raju, Arvind, Thimmanaik, Tara, Biswas, Sovan
In this work we explore the application of AI to robotic welding. Robotic welding is a widely used technology in many industries, but robots currently do not have the capability to detect welding defects which get introduced due to various reasons in
Externí odkaz:
http://arxiv.org/abs/2409.02290
Autor:
Xin, Bowen, Young, Tony, Wainwright, Claire E, Blake, Tamara, Lebrat, Leo, Gaass, Thomas, Benkert, Thomas, Stemmer, Alto, Coman, David, Dowling, Jason
Medical image synthesis generates additional imaging modalities that are costly, invasive or harmful to acquire, which helps to facilitate the clinical workflow. When training pairs are substantially misaligned (e.g., lung MRI-CT pairs with respirato
Externí odkaz:
http://arxiv.org/abs/2408.09432
Autor:
Cohen, Edith, Kaplan, Haim, Mansour, Yishay, Moran, Shay, Nissim, Kobbi, Stemmer, Uri, Tsfadia, Eliad
We revisit the fundamental question of formally defining what constitutes a reconstruction attack. While often clear from the context, our exploration reveals that a precise definition is much more nuanced than it appears, to the extent that a single
Externí odkaz:
http://arxiv.org/abs/2405.15753
Gradient boosted decision trees have achieved remarkable success in several domains, particularly those that work with static tabular data. However, the application of gradient boosted models to signal processing is underexplored. In this work, we in
Externí odkaz:
http://arxiv.org/abs/2405.09305
One of the most basic problems for studying the "price of privacy over time" is the so called private counter problem, introduced by Dwork et al. (2010) and Chan et al. (2010). In this problem, we aim to track the number of events that occur over tim
Externí odkaz:
http://arxiv.org/abs/2403.00028
Autor:
Stemmer, Uri
Private Everlasting Prediction (PEP), recently introduced by Naor et al. [2023], is a model for differentially private learning in which the learner never publicly releases a hypothesis. Instead, it provides black-box access to a "prediction oracle"
Externí odkaz:
http://arxiv.org/abs/2401.04311
The Private Aggregation of Teacher Ensembles (PATE) framework is a versatile approach to privacy-preserving machine learning. In PATE, teacher models that are not privacy-preserving are trained on distinct portions of sensitive data. Privacy-preservi
Externí odkaz:
http://arxiv.org/abs/2312.02132