Search Results for author:
Found 5 papers, 0 papers with code
Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcity
On tabular data, a significant body of literature has shown that current deep learning (DL) models perform at best similarly to Gradient Boosted Decision Trees (GBDTs), while significantly underperforming them on outlier data.
On the Value of Behavioral Representations for Dense Retrieval
We consider text retrieval within dense representational space in real-world settings such as e-commerce search where (a) document popularity and (b) diversity of queries associated with a document have a skewed distribution.
A Fast Randomized Algorithm for Massive Text Normalization
In addition, FLAN does not require any annotated data or supervised learning.
A Study of Context Dependencies in Multi-page Product Search
In this paper, we study RF techniques based on both long-term and short-term context dependencies in multi-page product search.
Leverage Implicit Feedback for Context-aware Product Search
However, customers with little or no purchase history do not benefit from personalized product search.
