activity
20222025
most citedDeep Learning for Choice Modeling

6 citations · 15 across the 11 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.LG2023

Transformer Choice Net: A Transformer Neural Network for Choice Prediction

Hanzhao Wang, Xiaocheng Li, Kalyan Talluri

Discrete-choice models, such as Multinomial Logit, Probit, or Mixed-Logit, are widely used in Marketing, Economics, and Operations Research: given a set of alternatives, the custom…

stat.ML2023★ 2 cited

Learning to Make Adherence-Aware Advice

Guanting Chen, Xiaocheng Li, Chunlin Sun +1

As artificial intelligence (AI) systems play an increasingly prominent role in human decision-making, challenges surface in the realm of human-AI interactions. One challenge arises…

cs.AI2023★ 3 cited

A Neural Network Based Choice Model for Assortment Optimization

Hanzhao Wang, Zhongze Cai, Xiaocheng Li +1

Discrete-choice models are used in economics, marketing and revenue management to predict customer purchase probabilities, say as a function of prices and other features of the off…

cs.LG2023

When No-Rejection Learning is Consistent for Regression with Rejection

Xiaocheng Li, Shang Liu, Chunlin Sun +1

Learning with rejection has been a prototypical model for studying the human-AI interaction on prediction tasks. Upon the arrival of a sample instance, the model first uses a rejec…

cs.LG2023★ 1 cited

Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods

Shang Liu, Zhongze Cai, Xiaocheng Li

In this paper, we consider the uncertainty quantification problem for regression models. Specifically, we consider an individual calibration objective for characterizing the quanti…