papers

Publications (15)

math.NA2017

Successive Rank-One Approximations for Nearly Orthogonally Decomposable Symmetric Tensors

Cun Mu, Daniel Hsu, Donald Goldfarb

Many idealized problems in signal processing, machine learning and statistics can be reduced to the problem of finding the symmetric canonical decomposition of an underlying symmet…

cs.IR2024

Long or Short or Both? An Exploration on Lookback Time Windows of Behavioral Features in Product Search Ranking

Qi Liu, Atul Singh, Jingbo Liu +3

Customer shopping behavioral features are core to product search ranking models in eCommerce. In this paper, we investigate the effect of lookback time windows when aggregating the…

cs.IR2026

Scaling and Stabilizing Large-Scale Embedding-Based Retrieval

Zhen Yang, Juexin Lin, Hongwei Shang +8

Embedding-based retrieval (EBR) is foundational to large-scale e-commerce search, yet its effectiveness is often constrained by the quality of training signals and the representati…

cs.LG2019

An Empirical Comparison of FAISS and FENSHSES for Nearest Neighbor Search in Hamming Space

Cun Mu, Binwei Yang, Zheng Yan

In this paper, we compare the performances of FAISS and FENSHSES on nearest neighbor search in Hamming space--a fundamental task with ubiquitous applications in nowadays eCommerce.…

stat.ML2019

A Machine Learning Approach to Shipping Box Design

Guang Yang, Cun Mu

Having the right assortment of shipping boxes in the fulfillment warehouse to pack and ship customer's online orders is an indispensable and integral part of nowadays eCommerce bus…

cs.CL2023

LLM360: Towards Fully Transparent Open-Source LLMs

Zhengzhong Liu, Aurick Qiao, Willie Neiswanger +25

The recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers. However, most LLMs…