Results 11 to 20 of about 509,375 (328)
DP-MINIMAL VALUED FIELDS [PDF]
The Journal of Symbolic Logic, 2015 We show that dp-minimal valued fields are henselian and give classifications of dp-minimal ordered abelian groups and dp-minimal ordered fields without additional structure.
F. Jahnke, Pierre Simon, Erik Walsberg
semanticscholar +6 more sources
Notre Dame Journal of Formal Logic, 2014 We prove that in NTP_2 theories if p is a dependent type with dp-rank >= κ, then this can be witnessed by indiscernible sequences of tuples satisfying p. If p has dp-rank infinity, then this can be witnessed by singletons (in any theory).
Itay Kaplan, Pierre Simon
core +8 more sources
Outcomes and Risk Score for Distal Pancreatectomy with Celiac Axis Resection (DP-CAR): An International Multicenter Analysis [PDF]
Annals of Surgical Oncology, 2019 BackgroundDistal pancreatectomy with celiac axis resection (DP-CAR) is a treatment option for selected patients with pancreatic cancer involving the celiac axis.
S. Klompmaker +26 more
semanticscholar +3 more sources
DP-MINIMALITY: INVARIANT TYPES AND DP-RANK [PDF]
The Journal of Symbolic Logic, 2014 AbstractThis paper has two parts. In the first one, we prove that an invariant dp-minimal type is either finitely satisfiable or definable. We also prove that a definable version of the (p,q)-theorem holds in dp-minimal theories of small or medium directionality.In the second part, we study dp-rank in dp-minimal theories and show that it enjoys many ...
Simon, Pierre
openaire +4 more sources
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy [PDF]
Journal of Artificial Intelligence Research, 2023 Machine Learning (ML) models are ubiquitous in real-world applications and are a constant focus of research. Modern ML models have become more complex, deeper, and harder to reason about.
N. Ponomareva +8 more
semanticscholar +1 more source
DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass [PDF]
Conference on Computer and Communications Security, 2023 Differentially private stochastic gradient descent (DP-SGD) adds noise to gradients in back-propagation, safeguarding training data from privacy leakage, particularly membership inference.
Minxin Du +5 more
semanticscholar +1 more source
Bounding Training Data Reconstruction in DP-SGD [PDF]
Neural Information Processing Systems, 2023 Differentially private training offers a protection which is usually interpreted as a guarantee against membership inference attacks. By proxy, this guarantee extends to other threats like reconstruction attacks attempting to extract complete training ...
Jamie Hayes +2 more
semanticscholar +1 more source
DP-NeRF: Deblurred Neural Radiance Field with Physical Scene Priors [PDF]
Computer Vision and Pattern Recognition, 2022 Neural Radiance Field (NeRF) has exhibited outstanding three-dimensional (3D) reconstruction quality via the novel view synthesis from multi-view images and paired calibrated camera parameters.
Dogyoon Lee +3 more
semanticscholar +1 more source
DP Compress: A Model Compression Scheme for Generating Efficient Deep Potential Models. [PDF]
Journal of Chemical Theory and Computation, 2021 Machine-learning-based interatomic potential energy surface (PES) models are revolutionizing the field of molecular modeling. However, although much faster than electronic structure schemes, these models suffer from costly computations via deep neural ...
Denghui Lu +6 more
semanticscholar +1 more source
Feasibility of papaya merah delima farming in suburb area of Manado City [PDF]
E3S Web of Conferences, 2021 A Research has been conducted in Pandu Experimental Garden, Talawaan Bantik Village, North Sulawesi, in 2017-2019. It is located in suburb area of Manado City having high demand of fruits, mainly papaya The objectiveness of the research was to analyze ...
Malia Ibrahim Erik +5 more
doaj +1 more source