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08/13/2023
TextDiff: Mask-Guided Residual Diffusion Models for Scene Text Image Super-Resolution
The goal of scene text image super-resolution is to reconstruct high-res...
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04/25/2023
COUPA: An Industrial Recommender System for Online to Offline Service Platforms
Aiming at helping users locally discovery retail services (e.g., enterta...
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10/24/2022
A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems
Assigning items to owners is a common problem found in various real-worl...
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09/18/2022
A Benchmark for Understanding and Generating Dialogue between Characters in Stories
Many classical fairy tales, fiction, and screenplays leverage dialogue t...
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04/20/2022
A Corpus for Understanding and Generating Moral Stories
Teaching morals is one of the most important purposes of storytelling. A...
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01/21/2022
Robust Unsupervised Graph Representation Learning via Mutual Information Maximization
Recent studies have shown that GNNs are vulnerable to adversarial attack...
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01/19/2022
RunnerDNA: Interpretable indicators and model to characterize human activity pattern and individual difference
Human activity analysis based on sensor data plays a significant role in...
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12/28/2021
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
In federated learning (FL) problems, client sampling plays a key role in...
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10/27/2021
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data
Time series forecasting is widely used in business intelligence, e.g., f...
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10/22/2021
PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method
Graph convolutional networks (GCNs) have been widely adopted for graph r...
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02/03/2021
LinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign
A lot of online marketing campaigns aim to promote user interaction. The...
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07/22/2020
Multi-scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains
In this paper, we propose novel multi-scale DNNs (MscaleDNN) using the i...
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06/10/2020
Bandit Samplers for Training Graph Neural Networks
Several sampling algorithms with variance reduction have been proposed f...
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05/25/2020
Privacy-Preserving Graph Neural Network for Node Classification
Recently, Graph Neural Network (GNN) has achieved remarkable progresses ...
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03/12/2020
Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization
Points of interest (POI) recommendation has been drawn much attention re...
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03/05/2020
InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance
The insurance industry has been creating innovative products around the ...
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02/29/2020
Robotic Cane as a Soft SuperLimb for Elderly Sit-to-Stand Assistance
Many researchers have identified robotics as a potential solution to the...
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02/27/2020
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing
Mobile payment such as Alipay has been widely used in our daily lives. T...
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02/27/2020
Heterogeneous Graph Neural Networks for Malicious Account Detection
We present, GEM, the first heterogeneous graph neural network approach f...
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02/27/2020
Uncovering Insurance Fraud Conspiracy with Network Learning
Fraudulent claim detection is one of the greatest challenges the insuran...
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02/27/2020
DSSLP: A Distributed Framework for Semi-supervised Link Prediction
Link prediction is widely used in a variety of industrial applications, ...
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02/27/2020
How Much Can A Retailer Sell? Sales Forecasting on Tmall
Time-series forecasting is an important task in both academic and indust...
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12/26/2019
A Time Attention based Fraud Transaction Detection Framework
With online payment platforms being ubiquitous and important, fraud tran...
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09/18/2018
Model-Protected Multi-Task Learning
Multi-task learning (MTL) refers to the paradigm of learning multiple re...
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05/11/2018
Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud
Internet companies are facing the need of handling large scale machine l...
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04/17/2018
Feature Propagation on Graph: A New Perspective to Graph Representation Learning
We study feature propagation on graph, an inference process involved in ...
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04/13/2018
Distributed Collaborative Hashing and Its Applications in Ant Financial
Collaborative filtering, especially latent factor model, has been popula...
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02/03/2018
GeniePath: Graph Neural Networks with Adaptive Receptive Paths
We present, GeniePath, a scalable approach for learning adaptive recepti...
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05/06/2015