output
20122024
most citedOn Application of Learning to Rank for E-Commerce Search

143 citations

Showing cs.LGShow all

8 papers · 1 filter

cs.LG2021

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…

cs.LG20201 cited

Probabilistic Outlier Detection and Generation

Stefano Giovanni Rizzo, Linsey Pang, Yixian Chen +1

A new method for outlier detection and generation is introduced by lifting data into the space of probability distributions which are not analytically expressible, but from which s…

cs.LG20201 cited

On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs

Behzad Shahrasbi, Venugopal Mani, Apoorv Reddy Arrabothu +3

Recommender systems are an essential part of any e-commerce platform. Recommendations are typically generated by aggregating large amounts of user data. A malicious actor may be mo…

cs.LG2020

G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling

Souradip Chakraborty, Aritra Roy Gosthipaty, Sayak Paul

In the realms of computer vision, it is evident that deep neural networks perform better in a supervised setting with a large amount of labeled data. The representations learned wi…

cs.LG201935 cited

Self-attention with Functional Time Representation Learning

Da Xu, Chuanwei Ruan, Sushant Kumar +2

Sequential modelling with self-attention has achieved cutting edge performances in natural language processing. With advantages in model flexibility, computation complexity and int…

cs.LG201972 cited

Product Knowledge Graph Embedding for E-commerce

Da Xu, Chuanwei Ruan, Evren Korpeoglu +2

In this paper, we propose a new product knowledge graph (PKG) embedding approach for learning the intrinsic product relations as product knowledge for e-commerce. We define the key…