Results 101 to 110 of about 8,464,096 (315)
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source
On Parameter Tuning for Spectral Clustering: Two Simple, Fast, and Effective Criteria
Spectral clustering is a modern clustering approach with many successful applications such as image segmentation and document grouping. However, it has faced two major challenges – high computational complexity and sensitivity of a scale parameter
Guangliang Chen +2 more
doaj +1 more source
Cross section, final spin and zoom-whirl behavior in high-energy black hole collisions
We study the collision of two highly boosted equal mass, nonrotating black holes with generic impact parameter. We find such systems to exhibit zoom-whirl behavior when fine tuning the impact parameter.
E. Witten +9 more
core +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source
TRACE: Time Series Parameter Efficient Fine-Tuning
We propose an efficient fine-tuning method for time series foundation models, termed TRACE: Time Series Parameter Efficient Fine-tuning. While pretrained time series foundation models are gaining popularity, they face the following challenges: (1) Unlike natural language tasks, time series data vary in frequency, channel numbers, historical/prediction ...
Yuze Li, Wei Zhu
openaire +2 more sources
Current Tracking Adaptive Control of Brushless DC Motors
In this paper, the current tracking for Brushless Direct Current motors is approached considering uncertainty in the parameters of the motor's model. An adaptive control scheme to compensate electrical parameters uncertainty is proposed without requiring any knowledge of the mechanical parameters.
Fernanda Ramos‐García +3 more
wiley +1 more source
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley +1 more source
Parameter-efficient fine-tuning of large language models using semantic knowledge tuning
Large Language Models (LLMs) are gaining significant popularity in recent years for specialized tasks using prompts due to their low computational cost. Standard methods like prefix tuning utilize special, modifiable tokens that lack semantic meaning and
Nusrat Jahan Prottasha +6 more
doaj +1 more source
Measuring Fine Tuning In Supersymmetry
The solution to fine tuning is one of the principal motivations for supersymmetry. However constraints on the parameter space of the Minimal Supersymmetric Standard Model (MSSM) suggest it may also require fine tuning (although to a much lesser extent ...
Athron, Peter, Miller, D. J.
core

