10 citations · 19 across the 6 of their papers we have counts for
7 papers
TabEmb: Joint Semantic-Structure Embedding for Table Annotation
Ehsan Hoseinzade, Ke Wang, Anandharaju Durai Raju
Table annotation is crucial for making web and enterprise tables usable in downstream NLP applications. Unlike textual data where learning semantically rich token or sentence embed…
ZTab: Domain-based Zero-shot Annotation for Table Columns
Ehsan Hoseinzade, Ke Wang
This study addresses the challenge of automatically detecting semantic column types in relational tables, a key task in many real-world applications. Zero-shot modeling eliminates…
Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction
Ali Mehrabian, Ehsan Hoseinzade, Mahdi Mazloum +1
Stock markets play an important role in the global economy, where accurate stock price predictions can lead to significant financial returns. While existing transformer-based model…
Graph Neural Network Approach to Semantic Type Detection in Tables
Ehsan Hoseinzade, Ke Wang
This study addresses the challenge of detecting semantic column types in relational tables, a key task in many real-world applications. While language models like BERT have improve…
Representation Extraction and Deep Neural Recommendation for Collaborative Filtering
Arash Khoeini, Saman Haratizadeh, Ehsan Hoseinzade
Many Deep Learning approaches solve complicated classification and regression problems by hierarchically constructing complex features from the raw input data. Although a few works…
U-CNNpred: A Universal CNN-based Predictor for Stock Markets
Ehsan Hoseinzade, Saman Haratizadeh, Arash Khoeini
The performance of financial market prediction systems depends heavily on the quality of features it is using. While researchers have used various techniques for enhancing the stoc…