by instadatahelp | Sep 1, 2023 | AI Blogs
Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data Authors: Vaidotas Simkus, Benjamin Rhodes, Michael U. Gutmann; Journal of Machine Learning Research, 24(196):1−72, 2023. Abstract Statistical models play a crucial role in machine...
by instadatahelp | Sep 1, 2023 | AI Blogs
Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation Cynthia Rudin, Yaron Shaposhnik; 24(16):1−44, 2023. Abstract This study presents a novel method for comprehending specific predictions made by global...
![Combining Deep Inductive Logic Programming with Reinforcement Learning (arXiv:2308.16210v1 [cs.LG])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Sep 1, 2023 | AI Blogs
One way to explain the hierarchical levels of understanding in a machine learning model is through the use of inductive logic programming (ILP), which is a data efficient approach capable of learning logical rules that can capture data behavior. A variation of ILP,...
by instadatahelp | Sep 1, 2023 | AI Blogs
Contrasting Identifying Assumptions of Average Causal Effects: Robustness and Semiparametric Efficiency Tetiana Gorbach, Xavier de Luna, Juha Karvanen, Ingeborg Waernbaum; 24(197):1−65, 2023. Abstract This paper examines different identifying assumptions for...
by instadatahelp | Sep 1, 2023 | AI Blogs
The content can be rewritten as: Emotion recognition using electroencephalogram (EEG) encompasses two main scenarios: classifying discrete labels and regressing continuously tagged labels. While numerous algorithms have been proposed for classification tasks, there...
by instadatahelp | Sep 1, 2023 | AI Blogs
Interpolating Classifiers with Few Mistakes Tengyuan Liang and Benjamin Recht; 24(20):1−27, 2023. Abstract This paper presents a basic analysis of the regret and generalization capabilities of minimum-norm interpolating classifiers (MNIC). MNIC is a function that...
by instadatahelp | Sep 1, 2023 | AI Blogs
The following content is about a paper titled “Learning Collaborative Information Dissemination with Graph-based Multi-Agent Reinforcement Learning” written by Raffaele Galliera and three other authors. The paper discusses the importance of efficient and...
by instadatahelp | Sep 1, 2023 | AI Blogs
CodaLab Competitions: An Open Source Platform for Organizing Scientific Challenges Authors: Adrien Pavao, Isabelle Guyon, Anne-Catherine Letournel, Dinh-Tuan Tran, Xavier Baro, Hugo Jair Escalante, Sergio Escalera, Tyler Thomas, Zhen Xu; Published in 24(198):1−6,...
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...
