research
∙
06/28/2023
Pb-Hash: Partitioned b-bit Hashing
Many hashing algorithms including minwise hashing (MinHash), one permuta...
share
research
∙
06/28/2023
Blockwise Feature Interaction in Recommendation Systems
Feature interactions can play a crucial role in recommendation systems a...
research
∙
06/13/2023
Practice with Graph-based ANN Algorithms on Sparse Data: Chi-square Two-tower model, HNSW, Sign Cauchy Projections
Sparse data are common. The traditional “handcrafted” features are often...
research
∙
04/26/2023
Building K-Anonymous User Cohorts with Consecutive Consistent Weighted Sampling (CCWS)
To retrieve personalized campaigns and creatives while protecting user p...
research
∙
11/01/2022
Asymmetric Hashing for Fast Ranking via Neural Network Measures
Fast item ranking is an important task in recommender systems. In previo...
research
∙
10/26/2022
Constrained Approximate Similarity Search on Proximity Graph
Search engines and recommendation systems are built to efficiently displ...
research
∙
07/18/2022
Package for Fast ABC-Boost
This report presents the open-source package which implements the series...
research
∙
07/18/2022
pGMM Kernel Regression and Comparisons with Boosted Trees
In this work, we demonstrate the advantage of the pGMM (“powered general...
research
∙
06/22/2022
Proximity Graph Maintenance for Fast Online Nearest Neighbor Search
Approximate Nearest Neighbor (ANN) search is a fundamental technique for...
research
∙
05/30/2022
Integrity Authentication in Tree Models
Tree models are very widely used in practice of machine learning and dat...
research
∙
05/22/2022
Fast ABC-Boost: A Unified Framework for Selecting the Base Class in Multi-Class Classification
The work in ICML'09 showed that the derivatives of the classical multi-c...
research
∙
01/07/2022
GCWSNet: Generalized Consistent Weighted Sampling for Scalable and Accurate Training of Neural Networks
We develop the "generalized consistent weighted sampling" (GCWS) for has...
research
∙
01/05/2022
Communication-Efficient TeraByte-Scale Model Training Framework for Online Advertising
Click-Through Rate (CTR) prediction is a crucial component in the online...
research
∙
08/05/2020
F2GAN: Fusing-and-Filling GAN for Few-shot Image Generation
In order to generate images for a given category, existing deep generati...
research
∙
03/12/2020
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems
Neural networks of ads systems usually take input from multiple resource...
research
∙
11/24/2019
Image Cropping with Composition and Saliency Aware Aesthetic Score Map
Aesthetic image cropping is a practical but challenging task which aims ...
research
∙
05/16/2019
Inductive Guided Filter: Real-time Deep Image Matting with Weakly Annotated Masks on Mobile Devices
Recently, significant progress has been achieved in deep image matting. ...
research
∙
03/16/2018
