Search Results for author:
Found 8 papers, 4 papers with code
Multilingual Search with Subword TF-IDF
Multilingual search can be achieved with subword tokenization.
Question Generation by Transformers
A machine learning model was developed to automatically generate questions from Wikipedia passages using transformers, an attention-based model eschewing the paradigm of existing recurrent neural networks (RNNs).
Transfer Learning Robustness in Multi-Class Categorization by Fine-Tuning Pre-Trained Contextualized Language Models
This study compares the effectiveness and robustness of multi-class categorization of Amazon product data using transfer learning on pre-trained contextualized language models.
Multi-Label Product Categorization Using Multi-Modal Fusion Models
In this study, we investigated multi-modal approaches using images, descriptions, and titles to categorize e-commerce products on Amazon.
Attending to Mathematical Language with Transformers
Mathematical expressions were generated, evaluated and used to train neural network models based on the transformer architecture.
A Collaborative Approach to Angel and Venture Capital Investment Recommendations
With a similar model, the same dataset was used to generate investor recommendations for companies undergoing fundraising, which achieved highest prediction accuracy of 11. 1%.
Comparing heterogeneous entities using artificial neural networks of trainable weighted structural components and machine-learned activation functions
The model was used for matching news articles and videos, where the inputs and activation functions respectively consisted of term vectors and cosine similarity measures between the weighted structural components.
Churn analysis using deep convolutional neural networks and autoencoders
Customer temporal behavioral data was represented as images in order to perform churn prediction by leveraging deep learning architectures prominent in image classification.
