72 citations · 171 across the 16 of their papers we have counts for
8 papers · 1 filter
Pretrained Embeddings for E-commerce Machine Learning: When it Fails and Why?
Da Xu, Bo Yang
The use of pretrained embeddings has become widespread in modern e-commerce machine learning (ML) systems. In practice, however, we have encountered several key issues when using p…
Towards Robust Off-policy Learning for Runtime Uncertainty
Da Xu, Yuting Ye, Chuanwei Ruan +1
Off-policy learning plays a pivotal role in optimizing and evaluating policies prior to the online deployment. However, during the real-time serving, we observe varieties of interv…
A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
Sequential deep learning models such as RNN, causal CNN and attention mechanism do not readily consume continuous-time information. Discretizing the temporal data, as we show, caus…
Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
The recent paper by Byrd & Lipton (2019), based on empirical observations, raises a major concern on the impact of importance weighting for the over-parameterized deep learning mod…
Theoretical Understandings of Product Embedding for E-commerce Machine Learning
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
Product embeddings have been heavily investigated in the past few years, serving as the cornerstone for a broad range of machine learning applications in e-commerce. Despite the em…
Inductive Representation Learning on Temporal Graphs
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
Inductive representation learning on temporal graphs is an important step toward salable machine learning on real-world dynamic networks. The evolving nature of temporal dynamic gr…