
SHORING: Design Provable Conditional HighOrder Interaction Network via Symbolic Testing
Deep learning provides a promising way to extract effective representati...
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Question Directed Graph Attention Network for Numerical Reasoning over Text
Numerical reasoning over texts, such as addition, subtraction, sorting a...
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Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection
With the explosive growth of ecommerce, online transaction fraud has be...
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Bandit Samplers for Training Graph Neural Networks
Several sampling algorithms with variance reduction have been proposed f...
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Riemannian Proximal Policy Optimization
In this paper, We propose a general Riemannian proximal optimization alg...
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A Riemannian Primaldual 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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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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Intention Propagation for Multiagent Reinforcement Learning
A hallmark of an AI agent is to mimic human beings to understand and int...
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NetDP: An IndustrialScale 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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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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RNE: A Scalable Network Embedding for Billionscale Recommendation
Nowadays designing a real recommendation system has been a critical prob...
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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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Practical Privacy Preserving POI Recommendation
PointofInterest (POI) recommendation has been extensively studied and ...
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InfDetect: a Large Scale Graphbased Fraud Detection System for ECommerce Insurance
The insurance industry has been creating innovative products around the ...
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Long ShortTerm Sample Distillation
In the past decade, there has been substantial progress at training incr...
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A Semisupervised Graph Attentive Network for Financial Fraud Detection
With the rapid growth of financial services, fraud detection has been a ...
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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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Uncovering Insurance Fraud Conspiracy with Network Learning
Fraudulent claim detection is one of the greatest challenges the insuran...
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How Much Can A Retailer Sell? Sales Forecasting on Tmall
Timeseries forecasting is an important task in both academic and indust...
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Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Markov Logic Networks (MLNs), which elegantly combine logic rules and pr...
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TitAnt: Online Realtime Transaction Fraud Detection in Ant Financial
With the explosive growth of ecommerce and the booming of epayment, de...
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Can Graph Neural Networks Help Logic Reasoning?
Effectively combining logic reasoning and probabilistic inference has be...
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CostEffective Incentive Allocation via Structured Counterfactual Inference
We address a practical problem ubiquitous in modern industry, in which a...
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Value Propagation for Decentralized Networked Deep Multiagent Reinforcement Learning
We consider the networked multiagent reinforcement learning (MARL) prob...
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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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Neural ModelBased Reinforcement Learning for Recommendation
There are great interests as well as many challenges in applying reinfor...
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Double Neural Counterfactual Regret Minimization
Counterfactual Regret Minimization (CRF) is a fundamental and effective ...
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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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Latent Dirichlet Allocation for Internet Price War
Internet market makers are always facing intense competitive environment...
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Asynchronous Distributed Variational Gaussian Processes for Regression
Gaussian processes (GPs) are powerful nonparametric function estimators...
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Distributed Flexible Nonlinear Tensor Factorization
Tensor factorization is a powerful tool to analyse multiway data. Compa...
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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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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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Message passing with relaxed moment matching
Bayesian learning is often hampered by large computational expense. As a...
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EigenGP: Sparse Gaussian process models with datadependent eigenfunctions
Gaussian processes (GPs) provide a nonparametric representation of funct...
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Yuan Qi
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