论文题目:A Novel Hyperparameter-Free Approach to Decision Tree Construction That Avoids Overfitting by Design 引用信息:R. García Leiva, A. Fernández Anta, V. Mancuso and P. Casari, "A Novel Hyperparameter-Free Approach to Decision Tree Construction That Avoids Overfitting by Design," in IEEE...
In this paper, we propose a simple and computationally efficient, hyperparameter-free method that uses cosine similarity. Although recent studies show its effectiveness for metric learning, it remains uncertain if cosine similarity works well also for OOD detection. There are several differences in ...
SPICE and LIKES: Two hyperparameter-free methods for sparse-parameter estimation SPICE (arse terative ovariance-based stimation) is a recently introduced method for sparse-parameter estimation in linear models using a robust covariance ... P Stoica,P Babu - 《Signal Processing》 被引量: 179发表...
This work proposes novel hyperparameter-free losses for single view 3D reconstruction with morphable models (3DMM). We dispense with the hyperparameters used in other works by exploiting geometry, so that the shape of the object and the camera pose are jointly optimized in a sole term expression...
However, existing methods employ additional tunable hyperparameters on the server to determine the scaling factor. A contrasting approach is automated scaling analogous to tuning-free step-size schemes in stochastic gradient descent (SGD) methods, which offer competitive convergence rates and exhibit good...
To solve the above problems, a novel plug-and-play hyperparameter-free attention module (HFAM) based on feature map mathematical calculation is proposed in this work. HFAM uses statistical indicators to quantitatively characterize the fluctuations of feature maps that can accurately locate key ...
The findings of this study underscore the significance of hyperparameter optimization as a critical factor in elevating the predictive precision of freeway crashes. Keywords: boosting ensemble learning; machine learning; Shapley Additive Explanations (SHAP); freeway crash; traffic conditions...
A computing device determines hyperparameter values for outlier detection. An LOF score is computed for observation vectors using a neighborhood size value. Outlier observation vect
United States Patent US11561946 Note: If you have problems viewing the PDF, please make sure you have the latest version ofAdobe Acrobat. Back to full text
We provide a hyper-parameter-free algorithm for learning the DBT from data, and propose a new initialization method to enforce convergence to good solutions. Our findings provide some theoretical evidence for why a deep model might be beneficial. Experimental results on benchmark data show, that ...