papers

Publications (6)

stat.ML2025

Metadata Extraction Leveraging Large Language Models

Cuize Han, Sesh Jalagam

The advent of Large Language Models has revolutionized tasks across domains, including the automation of legal document analysis, a critical component of modern contract management…

stat.ML2021

Aggregated Customer Engagement Model

Priya Gupta, Cuize Han

E-commerce websites use machine learned ranking models to serve shopping results to customers. Typically, the websites log the customer search events, which include the query enter…

cs.IR2023

Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach

Tao Yang, Cuize Han, Chen Luo +3

Ranking is at the core of many artificial intelligence (AI) applications, including search engines, recommender systems, etc. Modern ranking systems are often constructed with lear…

stat.ML2021

IB-GAN: A Unified Approach for Multivariate Time Series Classification under Class Imbalance

Grace Deng, Cuize Han, Tommaso Dreossi +2

Classification of large multivariate time series with strong class imbalance is an important task in real-world applications. Standard methods of class weights, oversampling, or pa…

stat.ML2021

Scalable Feature Selection for (Multitask) Gradient Boosted Trees

Cuize Han, Nikhil Rao, Daria Sorokina +1

Gradient Boosted Decision Trees (GBDTs) are widely used for building ranking and relevance models in search and recommendation. Considerations such as latency and interpretability…

stat.ML2021

Extended Missing Data Imputation via GANs for Ranking Applications

Grace Deng, Cuize Han, David S. Matteson

We propose Conditional Imputation GAN, an extended missing data imputation method based on Generative Adversarial Networks (GANs). The motivating use case is learning-to-rank, the…