72 citations · 175 across the 16 of their papers we have counts for
22 papers
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
The recent work by Rendle et al. (2020), based on empirical observations, argues that matrix-factorization collaborative filtering (MCF) compares favorably to neural collaborative…
Variational Inference for Category Recommendation in E-Commerce platforms
Ramasubramanian Balasubramanian, Venugopal Mani, Abhinav Mathur +2
Category recommendation for users on an e-Commerce platform is an important task as it dictates the flow of traffic through the website. It is therefore important to surface precis…
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…
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…
GAN-based Recommendation with Positive-Unlabeled Sampling
Yao Zhou, Jianpeng Xu, Jun Wu +4
Recommender systems are popular tools for information retrieval tasks on a large variety of web applications and personalized products. In this work, we propose a Generative Advers…
A Real-Time Whole Page Personalization Framework for E-Commerce
Aditya Mantha, Anirudha Sundaresan, Shashank Kedia +6
E-commerce platforms consistently aim to provide personalized recommendations to drive user engagement, enhance overall user experience, and improve business metrics. Most e-commer…