Product Recommendation

34 papers with code • 1 benchmarks • 8 datasets

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Use these libraries to find Product Recommendation models and implementations
2 papers

Most implemented papers

Representation Learning for Attributed Multiplex Heterogeneous Network

cenyk1230/GATNE 5 May 2019

Network embedding (or graph embedding) has been widely used in many real-world applications.

Retrieving Similar E-Commerce Images Using Deep Learning

gofynd/mildnet 11 Jan 2019

In this paper, we propose a deep convolutional neural network for learning the embeddings of images in order to capture the notion of visual similarity.

TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network

mickeystroller/TaxoExpan 26 Jan 2020

Taxonomies consist of machine-interpretable semantics and provide valuable knowledge for many web applications.

A Tutorial on Thompson Sampling

iosband/ts_tutorial 7 Jul 2017

Thompson sampling is an algorithm for online decision problems where actions are taken sequentially in a manner that must balance between exploiting what is known to maximize immediate performance and investing to accumulate new information that may improve future performance.

MILDNet: A Lightweight Single Scaled Deep Ranking Architecture

gofynd/mildnet 3 Mar 2019

Inspired by the fact that successive CNN layers represent the image with increasing levels of abstraction, we compressed our deep ranking model to a single CNN by coupling activations from multiple intermediate layers along with the last layer.

Distributed Learning of Deep Neural Networks using Independent Subnet Training

BinhangYuan/IST_Release 4 Oct 2019

These properties of IST can cope with issues due to distributed data, slow interconnects, or limited device memory, making IST a suitable approach for cases of mandatory distribution.

Optimal Low-Rank Matrix Completion: Semidefinite Relaxations and Eigenvector Disjunctions

sean-lo/optimalmatrixcompletion.jl 20 May 2023

Low-rank matrix completion consists of computing a matrix of minimal complexity that recovers a given set of observations as accurately as possible.

Low-Rank Factorization of Determinantal Point Processes for Recommendation

mankmonjre/k-DPP-reco-engine 17 Feb 2016

In this work we present a new method for learning the DPP kernel from observed data using a low-rank factorization of this kernel.

Learning Compatibility Across Categories for Heterogeneous Item Recommendation

appier/compatibility-family-learning 31 Mar 2016

Identifying relationships between items is a key task of an online recommender system, in order to help users discover items that are functionally complementary or visually compatible.

RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising

criteo-research/reco-gym 2 Aug 2018

Recommender Systems are becoming ubiquitous in many settings and take many forms, from product recommendation in e-commerce stores, to query suggestions in search engines, to friend recommendation in social networks.