Product Recommendation

26 papers with code • 1 benchmarks • 6 datasets

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

Most implemented papers

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.

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.

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.

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.

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.

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.

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, and has numerous applications such as product recommendation.

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.

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.

Complete the Look: Scene-based Complementary Product Recommendation

kang205/STL-Dataset CVPR 2019

We design an approach to extract training data for this task, and propose a novel way to learn the scene-product compatibility from fashion or interior design images.