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06/22/2023
FuXi: A cascade machine learning forecasting system for 15-day global weather forecast
Over the past few years, due to the rapid development of machine learnin...
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11/03/2021
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation
Knowledge graph is generally incorporated into recommender systems to im...
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07/03/2021
SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing
Deep learning provides a promising way to extract effective representati...
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09/16/2020
Question Directed Graph Attention Network for Numerical Reasoning over Text
Numerical reasoning over texts, such as addition, subtraction, sorting a...
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08/08/2020
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection
With the explosive growth of e-commerce, online transaction fraud has be...
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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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05/19/2020
Riemannian Proximal Policy Optimization
In this paper, We propose a general Riemannian proximal optimization alg...
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05/19/2020
A Riemannian Primal-dual Algorithm Based on Proximal Operator and its Application in Metric Learning
In this paper, we consider optimizing a smooth, convex, lower semicontin...
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04/26/2020
SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling Check
Chinese Spelling Check (CSC) is a task to detect and correct spelling er...
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04/19/2020
Intention Propagation for Multi-agent Reinforcement Learning
A hallmark of an AI agent is to mimic human beings to understand and int...
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04/01/2020
NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay
Ant Credit Pay is a consumer credit service in Ant Financial Service Gro...
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03/12/2020
Local Contextual Attention with Hierarchical Structure for Dialogue Act Recognition
Dialogue act recognition is a fundamental task for an intelligent dialog...
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03/10/2020
RNE: A Scalable Network Embedding for Billion-scale Recommendation
Nowadays designing a real recommendation system has been a critical prob...
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03/10/2020
Generating Natural Language Adversarial Examples on a Large Scale with Generative Models
Today text classification models have been widely used. However, these c...
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03/05/2020
Practical Privacy Preserving POI Recommendation
Point-of-Interest (POI) recommendation has been extensively studied and ...
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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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03/02/2020
Long Short-Term Sample Distillation
In the past decade, there has been substantial progress at training incr...
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02/28/2020
A Semi-supervised Graph Attentive Network for Financial Fraud Detection
With the rapid growth of financial services, fraud detection has been a ...
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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
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
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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01/29/2020
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Markov Logic Networks (MLNs), which elegantly combine logic rules and pr...
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06/18/2019
TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial
With the explosive growth of e-commerce and the booming of e-payment, de...
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06/05/2019
Can Graph Neural Networks Help Logic Reasoning?
Effectively combining logic reasoning and probabilistic inference has be...
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02/07/2019
Cost-Effective Incentive Allocation via Structured Counterfactual Inference
We address a practical problem ubiquitous in modern industry, in which a...
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01/27/2019
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
We consider the networked multi-agent reinforcement learning (MARL) prob...
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12/27/2018
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System
There are great interests as well as many challenges in applying reinfor...
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12/27/2018
Neural Model-Based Reinforcement Learning for Recommendation
There are great interests as well as many challenges in applying reinfor...
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12/27/2018
Double Neural Counterfactual Regret Minimization
Counterfactual Regret Minimization (CRF) is a fundamental and effective ...
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11/26/2018
A Policy Gradient Method with Variance Reduction for Uplift Modeling
Uplift modeling aims to directly model the incremental impact of a treat...
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08/23/2018
Latent Dirichlet Allocation for Internet Price War
Internet market makers are always facing intense competitive environment...
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04/22/2017
Asynchronous Distributed Variational Gaussian Processes for Regression
Gaussian processes (GPs) are powerful non-parametric function estimators...
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04/27/2016
Distributed Flexible Nonlinear Tensor Factorization
Tensor factorization is a powerful tool to analyse multi-way data. Compa...
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11/12/2013
DinTucker: Scaling up Gaussian process models on multidimensional arrays with billions of elements
Infinite Tucker Decomposition (InfTucker) and random function prior mode...
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04/26/2013
Supervised Heterogeneous Multiview Learning for Joint Association Study and Disease Diagnosis
Given genetic variations and various phenotypical traits, such as Magnet...
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04/18/2012
Message passing with relaxed moment matching
Bayesian learning is often hampered by large computational expense. As a...
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04/18/2012