![Clustering in the Absence of an Eigengap: A Study (arXiv:2308.15642v1 [cs.LG])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Sep 1, 2023 | AI Blogs
In our research, we focus on graph clustering in the Stochastic Block Model (SBM) where there are both large clusters and small, unrecoverable clusters. Previous methods for exact recovery either do not allow small clusters of size less than the square root of the...
by instadatahelp | Aug 31, 2023 | AI Blogs
Calibrated Multiple-Output Quantile Regression with Representation Learning Authors: Shai Feldman, Stephen Bates, Yaniv Romano; Journal of Machine Learning Research, 24(24):1−48, 2023. Abstract We present a novel method for generating predictive regions that encompass...
by instadatahelp | Aug 31, 2023 | AI Blogs
The identification of constitutive parameters in engineering and biological materials, especially those with complex geometries and mechanical behaviors, has long been a challenge. The emergence of Physics-Informed Neural Networks (PINNs) has provided promising...
by instadatahelp | Aug 31, 2023 | AI Blogs
Q-Learning for MDPs with General Spaces: Convergence and Near Optimality via Quantization under Weak Continuity Authors: Ali Kara, Naci Saldi, Serdar Yüksel; Volume 24, Issue 199, Pages 1-34, 2023. Abstract This paper explores the applicability of reinforcement...
by instadatahelp | Aug 31, 2023 | AI Blogs
Artificial Intelligence has experienced a surge in interest in the last decade, largely due to the advancements in Deep Learning. Deep learning researchers have achieved great success in image processing through the use of Convolutional Neural Networks (CNNs)....
by instadatahelp | Aug 31, 2023 | AI Blogs
Impact of Classification Difficulty on the Spectra of Weight Matrices in Deep Learning and its Application to Early Stopping Xuran Meng, Jeff Yao; 24(28):1−40, 2023. Abstract Recent research has focused on understanding the success of deep learning. Random Matrix...
