479 citations · 1.9k across the 94 of their papers we have counts for
15 papers · 1 filter
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications
Rong Zhu, Andreas Pfadler, Ziniu Wu +6
Structure Learning for Bayesian network (BN) is an important problem with extensive research. It plays central roles in a wide variety of applications in Alibaba Group. However, ex…
FSPN: A New Class of Probabilistic Graphical Model
Ziniu Wu, Rong Zhu, Andreas Pfadler +5
We introduce factorize sum split product networks (FSPNs), a new class of probabilistic graphical models (PGMs). FSPNs are designed to overcome the drawbacks of existing PGMs in te…
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation
Rong Zhu, Ziniu Wu, Yuxing Han +5
Query optimizers rely on accurate cardinality estimation (CardEst) to produce good execution plans. The core problem of CardEst is how to model the rich joint distribution of attri…
MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions
Wenqi Jiang, Zhenhao He, Shuai Zhang +9
Deep neural networks are widely used in personalized recommendation systems. Unlike regular DNN inference workloads, recommendation inference is memory-bound due to the many random…
Tempura: A General Cost Based Optimizer Framework for Incremental Data Processing (Extended Version)
Zuozhi Wang, Kai Zeng, Botong Huang +10
Incremental processing is widely-adopted in many applications, ranging from incremental view maintenance, stream computing, to recently emerging progressive data warehouse and inte…
Strengthening Order Preserving Encryption with Differential Privacy
Amrita Roy Chowdhury, Bolin Ding, Somesh Jha +2
Ciphertexts of an order-preserving encryption (OPE) scheme preserve the order of their corresponding plaintexts. However, OPEs are vulnerable to inference attacks that exploit this…
Poet: Product-oriented Video Captioner for E-commerce
Shengyu Zhang, Ziqi Tan, Jin Yu +6
In e-commerce, a growing number of user-generated videos are used for product promotion. How to generate video descriptions that narrate the user-preferred product characteristics…
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data
Yuexiang Xie, Zhen Wang, Yaliang Li +6
High-order interactive features capture the correlation between different columns and thus are promising to enhance various learning tasks on ubiquitous tabular data. To automate t…
Understanding Negative Sampling in Graph Representation Learning
Zhen Yang, Ming Ding, Chang Zhou +3
Graph representation learning has been extensively studied in recent years. Despite its potential in generating continuous embeddings for various networks, both the effectiveness a…
Comprehensive Information Integration Modeling Framework for Video Titling
Shengyu Zhang, Ziqi Tan, Jin Yu +6
In e-commerce, consumer-generated videos, which in general deliver consumers' individual preferences for the different aspects of certain products, are massive in volume. To recomm…
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems
Chang Zhou, Jianxin Ma, Jianwei Zhang +2
Deep candidate generation (DCG) that narrows down the collection of relevant items from billions to hundreds via representation learning has become prevalent in industrial recommen…
Taming the Expressiveness and Programmability of Graph Analytical Queries
Lu Qin, Longbin Lai, Kongzhang Hao +6
Graph database has enjoyed a boom in the last decade, and graph queries accordingly gain a lot of attentions from both the academia and industry. We focus on analytical queries in…
Learning to Hash with Graph Neural Networks for Recommender Systems
Qiaoyu Tan, Ninghao Liu, Xing Zhao +3
Graph representation learning has attracted much attention in supporting high quality candidate search at scale. Despite its effectiveness in learning embedding vectors for objects…
InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining
Junyang Lin, An Yang, Yichang Zhang +3
Multi-modal pretraining for learning high-level multi-modal representation is a further step towards deep learning and artificial intelligence. In this work, we propose a novel mod…
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search
Daoyuan Chen, Yaliang Li, Minghui Qiu +7
Large pre-trained language models such as BERT have shown their effectiveness in various natural language processing tasks. However, the huge parameter size makes them difficult to…