84 citations · 100 across the 33 of their papers we have counts for
11 papers · 1 filter
A Versioned Unified Graph Index for Dynamic Timestamp-Aware Nearest Neighbor Search
Jun Woo Chung, Weijie Zhao
We present TiGER (Time-Integrated Graph for Efficient Retrieval), a novel approach for performing fast time-aware approximate nearest neighbor searches on dynamic vector datasets w…
Automating Financial Statement Audits with Large Language Models
Rushi Wang, Jiateng Liu, Weijie Zhao +2
Financial statement auditing is essential for stakeholders to understand a company's financial health, yet current manual processes are inefficient and error-prone. Even with exten…
GUITAR: Gradient Pruning toward Fast Neural Ranking
Weijie Zhao, Shulong Tan, Ping Li
With the continuous popularity of deep learning and representation learning, fast vector search becomes a vital task in various ranking/retrieval based applications, say recommenda…
Blockwise Feature Interaction in Recommendation Systems
Weijie Zhao, Ping Li
Feature interactions can play a crucial role in recommendation systems as they capture complex relationships between user preferences and item characteristics. Existing methods suc…
Practice with Graph-based ANN Algorithms on Sparse Data: Chi-square Two-tower model, HNSW, Sign Cauchy Projections
Ping Li, Weijie Zhao, Chao Wang +3
Sparse data are common. The traditional ``handcrafted'' features are often sparse. Embedding vectors from trained models can also be very sparse, for example, embeddings trained vi…
Building K-Anonymous User Cohorts with\\ Consecutive Consistent Weighted Sampling (CCWS)
Xinyi Zheng, Weijie Zhao, Xiaoyun Li +1
To retrieve personalized campaigns and creatives while protecting user privacy, digital advertising is shifting from member-based identity to cohort-based identity. Under such iden…
Constrained Approximate Similarity Search on Proximity Graph
Weijie Zhao, Shulong Tan, Ping Li
Search engines and recommendation systems are built to efficiently display relevant information from those massive amounts of candidates. Typically a three-stage mechanism is emplo…
Asymmetric Hashing for Fast Ranking via Neural Network Measures
Khoa Doan, Shulong Tan, Weijie Zhao +1
Fast item ranking is an important task in recommender systems. In previous works, graph-based Approximate Nearest Neighbor (ANN) approaches have demonstrated good performance on it…
FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems
Weijie Zhao, Xuewu Jiao, Xinsheng Luo +3
Deep learning has been widely deployed for online ads systems to predict Click-Through Rate (CTR). Machine learning researchers and practitioners frequently retrain CTR models to t…
Proximity Graph Maintenance for Fast Online Nearest Neighbor Search
Zhaozhuo Xu, Weijie Zhao, Shulong Tan +2
Approximate Nearest Neighbor (ANN) search is a fundamental technique for (e.g.,) the deployment of recommender systems. Recent studies bring proximity graph-based methods into prac…
Communication-Efficient TeraByte-Scale Model Training Framework for Online Advertising
Weijie Zhao, Xuewu Jiao, Mingqing Hu +3
Click-Through Rate (CTR) prediction is a crucial component in the online advertising industry. In order to produce a personalized CTR prediction, an industry-level CTR prediction m…