For many board gamers, the biggest obstacle to getting a game to the table isn’t complexity or length, it’s finding the right group at the right time. Solo board games solve that problem by offering ...
Representation learning fundamentally determines the classification performance of models on tabular data. However, existing tabular data classification models typically focus on single-modal encoding ...
This paper focuses on the nonlinear correlation between investor sentiment and stock returns and conducts in-depth research with the aid of deep learning and text mining techniques. First of all, sort ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
Mitra departs from the norm by being pretrained exclusively on synthetic data. Rather than relying on the limited and heterogeneous nature of real-world tabular datasets, Amazon researchers engineered ...
The rapid evolution of railway systems, driven by digitization and the proliferation of Internet-of-Things (IoT) devices, has resulted in an unprecedented volume of diverse and complex data. This ...
In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...
1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...
Abstract: Despite the artificial intelligence (AI) revolution, deep learning has yet to achieve much success with tabular data due to heterogeneous feature space and limited sample sizes without ...
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