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09/06/2023
Enhancing Event Sequence Modeling with Contrastive Relational Inference
Neural temporal point processes(TPPs) have shown promise for modeling co...
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08/23/2023
Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders
Sequential recommenders have been widely used in industry due to their s...
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08/21/2023
Leveraging Large Language Models for Pre-trained Recommender Systems
Recent advancements in recommendation systems have shifted towards more ...
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08/21/2023
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
Recommendation systems aim to provide users with relevant suggestions, b...
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05/19/2023
ALT: An Automatic System for Long Tail Scenario Modeling
In this paper, we consider the problem of long tail scenario modeling wi...
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02/13/2023
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation
In recommendation scenarios, there are two long-standing challenges, i.e...
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11/01/2022
Robust Direct Learning for Causal Data Fusion
In the era of big data, the explosive growth of multi-source heterogeneo...
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01/08/2022
Expert Knowledge-guided Geometric Representation Learning for Magnetic Resonance Imaging-based Glioma Grading
Radiomics and deep learning have shown high popularity in automatic glio...
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08/18/2021
A Unified Framework for Cross-Domain and Cross-System Recommendations
Cross-Domain Recommendation (CDR) and Cross-System Recommendation (CSR) ...
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03/02/2021
Cross-Domain Recommendation: Challenges, Progress, and Prospects
To address the long-standing data sparsity problem in recommender system...
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12/13/2020
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction
In the Click-Through Rate (CTR) prediction scenario, user's sequential b...
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09/02/2020
Self-supervised Smoothing Graph Neural Networks
This paper studies learning node representations with GNNs for unsupervi...
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08/04/2020
Stable and accurate numerical methods for generalized Kirchhoff-Love plates
Efficient and accurate numerical algorithms are developed to solve a gen...
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03/16/2020
Interpretable MTL from Heterogeneous Domains using Boosted Tree
Multi-task learning (MTL) aims at improving the generalization performan...
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03/05/2020
SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks
Machine learning techniques have been widely applied in Internet compani...
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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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08/05/2019
Knowledge Isomorphism between Neural Networks
This paper aims to analyze knowledge isomorphism between pre-trained dee...
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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
A Boosting Framework of Factorization Machine
Recently, Factorization Machines (FM) has become more and more popular f...
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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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04/03/2018
Machine Learning-Assisted Least Loaded Routing to Improve Performance of Circuit-Switched Networks
The Least Loaded (LL) routing algorithm has been in recent decades the r...
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02/03/2018
