activity
20242026
most citedTransfer Learning for Nonparametric Contextual Dynamic Pricing

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ML2026

On Non-Stationary Dynamic Pricing: Adaptivity and Optimality

Feiyu Jiang, Zifeng Zhao

We study the contextual dynamic pricing problem under non-stationarity, where a firm sells products to sequentially arriving consumers that behave according to an unknown deman…

cs.LG2025

Learning Personalized Ad Impact via Contextual Reinforcement Learning under Delayed Rewards

Yuwei Cheng, Zifeng Zhao, Haifeng Xu

Online advertising platforms use automated auctions to connect advertisers with potential customers, requiring effective bidding strategies to maximize profits. Accurate ad impact…

stat.ML2025

Locally Private Nonparametric Contextual Multi-armed Bandits

Yuheng Ma, Feiyu Jiang, Zifeng Zhao +2

Motivated by privacy concerns in sequential decision-making on sensitive data, we address the challenge of nonparametric contextual multi-armed bandits (MAB) under local differenti…

cs.LG2025★ 1 cited

Transfer Learning for Nonparametric Contextual Dynamic Pricing

Fan Wang, Feiyu Jiang, Zifeng Zhao +1

Dynamic pricing strategies are crucial for firms to maximize revenue by adjusting prices based on market conditions and customer characteristics. However, designing optimal pricing…

cs.LG2024

Contextual Dynamic Pricing: Algorithms, Optimality, and Local Differential Privacy Constraints

Zifeng Zhao, Feiyu Jiang, Yi Yu

We study contextual dynamic pricing problems where a firm sells products to sequentially-arriving consumers, behaving according to an unknown demand model. The firm aims to min…

stat.ME2024

Predicting Future Change-points in Time Series

Chak Fung Choi, Chunxue Li, Chun Yip Yau +1

Change-point detection and estimation procedures have been widely developed in the literature. However, commonly used approaches in change-point analysis have mainly been focusing…

stat.CO2024

SNSeg: An R Package for Time Series Segmentation via Self-Normalization

Shubo Sun, Zifeng Zhao, Feiyu Jiang +1

Time series segmentation aims to identify potential change-points in a sequence of temporally dependent data, so that the original sequence can be partitioned into several homogene…