One of the strengths of the model is its competitive grade of interpretability which is a requisite in most of real applications. The proposed algorithm is compared to other well-known ordinal ...

With excellent representation power for complex data, deep neural networks (DNNs) based approaches are state-of-the-art for ordinal regression problem which aims to classify instances into ordinal ...

💬 LMTrajectory Framework 🗨️ Prompt-Based Approach: Moving away from conventional numerical regression models, we reframe the task into a prompt-based question-answering perspective. Social Reasoning ...

Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI-like chatbots so good at understanding and using words. The work is ...

The purpose of this study is to identify the socioeconomic and demographic factors associated with household food insecurity in Namibia by fitting an ordinal logistic regression model using the ...

The purpose of this study is to identify the socioeconomic and demographic factors associated with household food insecurity in Namibia by fitting an ordinal logistic regression model using the ...

At Secret Math Meeting, Researchers Struggle to Outsmart AI The world's leading mathematicians were stunned by how adept artificial intelligence is at doing their jobs ...