Ruiming Tang

Orcid: 0000-0002-9224-2431

According to our database1, Ruiming Tang authored at least 228 papers between 2011 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Large language models make sample-efficient recommender systems.
Frontiers Comput. Sci., April, 2025

Towards efficient and effective unlearning of large language models for recommendation.
Frontiers Comput. Sci., March, 2025

2024
Utility-Oriented Reranking with Counterfactual Context.
ACM Trans. Knowl. Discov. Data, September, 2024

A Comprehensive Survey on Automated Machine Learning for Recommendations.
Trans. Recomm. Syst., June, 2024

Embedding Compression in Recommender Systems: A Survey.
ACM Comput. Surv., May, 2024

A Survey on Bid Optimization in Real-Time Bidding Display Advertising.
ACM Trans. Knowl. Discov. Data, April, 2024

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation.
ACM Trans. Inf. Syst., January, 2024

AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation.
Knowl. Inf. Syst., January, 2024

Beyond Positive History: Re-ranking with List-level Hybrid Feedback.
CoRR, 2024

RevisEval: Improving LLM-as-a-Judge via Response-Adapted References.
CoRR, 2024

RethinkMCTS: Refining Erroneous Thoughts in Monte Carlo Tree Search for Code Generation.
CoRR, 2024

ToolACE: Winning the Points of LLM Function Calling.
CoRR, 2024

Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models.
CoRR, 2024

Performance Law of Large Language Models.
CoRR, 2024

Bridging and Modeling Correlations in Pairwise Data for Direct Preference Optimization.
CoRR, 2024

Prompt Tuning as User Inherent Profile Inference Machine.
CoRR, 2024

A Decoding Acceleration Framework for Industrial Deployable LLM-based Recommender Systems.
CoRR, 2024

Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation.
CoRR, 2024

All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era.
CoRR, 2024

Entropy Law: The Story Behind Data Compression and LLM Performance.
CoRR, 2024

CoIR: A Comprehensive Benchmark for Code Information Retrieval Models.
CoRR, 2024

ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation.
CoRR, 2024

LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation.
CoRR, 2024

LLM-enhanced Reranking in Recommender Systems.
CoRR, 2024

Extracting Essential and Disentangled Knowledge for Recommendation Enhancement.
CoRR, 2024

Evaluating the External and Parametric Knowledge Fusion of Large Language Models.
CoRR, 2024

Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation.
CoRR, 2024

Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation.
CoRR, 2024

CELA: Cost-Efficient Language Model Alignment for CTR Prediction.
CoRR, 2024

CodeGRAG: Extracting Composed Syntax Graphs for Retrieval Augmented Cross-Lingual Code Generation.
CoRR, 2024

WESE: Weak Exploration to Strong Exploitation for LLM Agents.
CoRR, 2024

Tired of Plugins? Large Language Models Can Be End-To-End Recommenders.
CoRR, 2024

Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models.
CoRR, 2024

ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems.
CoRR, 2024

Aligning Crowd Feedback via Distributional Preference Reward Modeling.
CoRR, 2024

Understanding the planning of LLM agents: A survey.
CoRR, 2024

D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems.
CoRR, 2024

Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges.
CoRR, 2024

M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation.
Proceedings of the ACM on Web Conference 2024, 2024

ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation.
Proceedings of the ACM on Web Conference 2024, 2024

ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction.
Proceedings of the ACM on Web Conference 2024, 2024

Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

LightCS: Selecting Quadratic Feature Crosses in Linear Complexity.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

HiFI: Hierarchical Fairness-aware Integrated Ranking with Constrained Reinforcement Learning.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Ranking-Aware Unbiased Post-Click Conversion Rate Estimation via AUC Optimization on Entire Exposure Space.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Multi-sourced Integrated Ranking with Exposure Fairness.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Active Explainable Recommendation with Limited Labeling Budgets.
Proceedings of the IEEE International Conference on Acoustics, 2024

MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Retrieval-Oriented Knowledge for Click-Through Rate Prediction.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

SINKT: A Structure-Aware Inductive Knowledge Tracing Model with Large Language Model.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Learning to Edit: Aligning LLMs with Knowledge Editing.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

D3: A Methodological Exploration of Domain Division, Modeling, and Balance in Multi-Domain Recommendations.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning to Retrieve User Behaviors for Click-through Rate Estimation.
ACM Trans. Inf. Syst., October, 2023

AIM: Automatic Interaction Machine for Click-Through Rate Prediction.
IEEE Trans. Knowl. Data Eng., April, 2023

Large-Scale Interactive Recommendation With Tree-Structured Reinforcement Learning.
IEEE Trans. Knowl. Data Eng., April, 2023

A Unified Framework for Multi-Domain CTR Prediction via Large Language Models.
CoRR, 2023

Music-PAW: Learning Music Representations via Hierarchical Part-whole Interaction and Contrast.
CoRR, 2023

Towards Automated Negative Sampling in Implicit Recommendation.
CoRR, 2023

ALT: Towards Fine-grained Alignment between Language and CTR Models for Click-Through Rate Prediction.
CoRR, 2023

Ten Challenges in Industrial Recommender Systems.
CoRR, 2023

Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation.
CoRR, 2023

Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction.
CoRR, 2023

Contrastive Multi-view Framework for Customer Lifetime Value Prediction.
CoRR, 2023

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models.
CoRR, 2023

How Can Recommender Systems Benefit from Large Language Models: A Survey.
CoRR, 2023

CTRL: Connect Tabular and Language Model for CTR Prediction.
CoRR, 2023

REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation.
CoRR, 2023

Multi-Task Deep Recommender Systems: A Survey.
CoRR, 2023

Integrated Ranking for News Feed with Reinforcement Learning.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Dynamically Expandable Graph Convolution for Streaming Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

Compressed Interaction Graph based Framework for Multi-behavior Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

AutoGen: An Automated Dynamic Model Generation Framework for Recommender System.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

A Bird's-eye View of Reranking: From List Level to Page Level.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

AutoML for Deep Recommender Systems: Fundamentals and Advances.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

FINAL: Factorized Interaction Layer for CTR Prediction.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Robust Causal Inference for Recommender System to Overcome Noisy Confounders.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Single-shot Feature Selection for Multi-task Recommendations.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

AutoTransfer: Instance Transfer for Cross-Domain Recommendations.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Customer Lifetime Value Prediction: Towards the Paradigm Shift of Recommender System Objectives.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with RecSys 2023.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

User Behavior Modeling with Deep Learning for Recommendation: Recent Advances.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

AutoOpt: Automatic Hyperparameter Scheduling and Optimization for Deep Click-through Rate Prediction.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

RLMixer: A Reinforcement Learning Approach for Integrated Ranking with Contrastive User Preference Modeling.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Optimal Transport for Treatment Effect Estimation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

On-device Integrated Re-ranking with Heterogeneous Behavior Modeling.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Deep Landscape Forecasting in Multi-Slot Real-Time Bidding.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Hierarchical Projection Enhanced Multi-behavior Recommendation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

A Survey on User Behavior Modeling in Recommender Systems.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Personalized Diversification for Neural Re-ranking in Recommendation.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Optimal Real-Time Bidding Strategy for Position Auctions in Online Advertising.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Diffusion Augmentation for Sequential Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

HAMUR: Hyper Adapter for Multi-Domain Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

DFFM: Domain Facilitated Feature Modeling for CTR Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Set-to-Sequence Ranking-Based Concept-Aware Learning Path Recommendation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Beyond Relevance Ranking: A General Graph Matching Framework for Utility-Oriented Learning to Rank.
ACM Trans. Inf. Syst., 2022

AutoHash: Learning Higher-Order Feature Interactions for Deep CTR Prediction.
IEEE Trans. Knowl. Data Eng., 2022

Click-through rate prediction using transfer learning with fine-tuned parameters.
Inf. Sci., 2022

A Brief History of Recommender Systems.
CoRR, 2022

Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation.
CoRR, 2022

Automated Machine Learning for Deep Recommender Systems: A Survey.
CoRR, 2022

Cross Pairwise Ranking for Unbiased Item Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation.
Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022


Hierarchical Imitation Learning via Subgoal Representation Learning for Dynamic Treatment Recommendation.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Improving Knowledge Tracing with Collaborative Information.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Multi-Behavior Sequential Transformer Recommender.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Multi-Level Interaction Reranking with User Behavior History.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

RankFlow: Joint Optimization of Multi-Stage Cascade Ranking Systems as Flows.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Neural Re-ranking for Multi-stage Recommender Systems.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

An Effective Post-training Embedding Binarization Approach for Fast Online Top-K Passage Matching.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022

Neural Re-ranking in Multi-stage Recommender Systems: A Review.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation.
Proceedings of the IEEE International Conference on Data Mining, 2022

Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Automatical Graph-based Knowledge Tracing.
Proceedings of the 15th International Conference on Educational Data Mining, 2022

Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Balancing Utility and Exposure Fairness for Integrated Ranking with Reinforcement Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

IntTower: The Next Generation of Two-Tower Model for Pre-Ranking System.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

LCD: Adaptive Label Correction for Denoising Music Recommendation.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Numerical Feature Representation with Hybrid <i>N</i>-ary Encoding.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation.
CoRR, 2021

Content Filtering Enriched GNN Framework for News Recommendation.
CoRR, 2021

Context-aware Reranking with Utility Maximization for Recommendation.
CoRR, 2021

Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning.
CoRR, 2021

AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction.
CoRR, 2021

QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback.
IEEE Access, 2021

An Adversarial Imitation Click Model for Information Retrieval.
Proceedings of the WWW '21: The Web Conference 2021, 2021

A Graph-Enhanced Click Model for Web Search.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Learning to Build High-Fidelity and Robust Environment Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

On Effective Scheduling of Model-based Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ModularNAS: Towards Modularized and Reusable Neural Architecture Search.
Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Retrieval & Interaction Machine for Tabular Data Prediction.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Dual Graph enhanced Embedding Neural Network for CTR Prediction.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

An Embedding Learning Framework for Numerical Features in CTR Prediction.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Deep Learning for Click-Through Rate Estimation.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Extracting Attentive Social Temporal Excitation for Sequential Recommendation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
State representation modeling for deep reinforcement learning based recommendation.
Knowl. Based Syst., 2020

Top-aware reinforcement learning based recommendation.
Neurocomputing, 2020

AutoDis: Automatic Discretization for Embedding Numerical Features in CTR Prediction.
CoRR, 2020

A Practical Incremental Method to Train Deep CTR Models.
CoRR, 2020

Personalized Re-ranking for Improving Diversity in Live Recommender Systems.
CoRR, 2020

Dual-attentional Factorization-Machines based Neural Network for User Response Prediction.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

End-to-End Deep Reinforcement Learning based Recommendation with Supervised Embedding.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Neighbor Interaction Aware Graph Convolution Networks for Recommendation.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Multi-Branch Convolutional Network for Context-Aware Recommendation.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Personalized Re-ranking with Item Relationships for E-commerce.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

U-rank: Utility-oriented Learning to Rank with Implicit Feedback.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

TGCN: Tag Graph Convolutional Network for Tag-Aware Recommendation.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019
Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data.
ACM Trans. Inf. Syst., 2019

Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction.
Proceedings of the World Wide Web Conference, 2019

Order-aware Embedding Neural Network for CTR Prediction.
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

PAL: a position-bias aware learning framework for CTR prediction in live recommender systems.
Proceedings of the 13th ACM Conference on Recommender Systems, 2019

A Novel KNN Approach for Session-Based Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Multi-graph Convolution Collaborative Filtering.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Optimizing Ranking Algorithm in Recommender System via Deep Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Advanced Manufacturing, 2019

Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling.
CoRR, 2018

An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation.
CoRR, 2018

DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction.
CoRR, 2018

Collaborative Filtering with Graph-based Implicit Feedback.
CoRR, 2018

Field-aware probabilistic embedding neural network for CTR prediction.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification.
Proceedings of the Database Systems for Advanced Applications, 2018

2017
Holistic Neural Network for CTR Prediction.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017

DeepFM: A Factorization-Machine based Neural Network for CTR Prediction.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

A Graph-Based Push Service Platform.
Proceedings of the Database Systems for Advanced Applications, 2017

2016
A Framework for Sampling-Based XML Data Pricing.
Trans. Large Scale Data Knowl. Centered Syst., 2016

On efficient conditioning of probabilistic relational databases.
Knowl. Based Syst., 2016

2015
Valuating Queries for Data Trading in Modern Cities.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

An efficient and truthful pricing mechanism for team formation in crowdsourcing markets.
Proceedings of the 2015 IEEE International Conference on Communications, 2015

Expressing and Processing Path-Centric XML Queries.
Proceedings of the Database and Expert Systems Applications, 2015

Mining target users for online marketing based on App Store data.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
An Efficient Conditioning Method for Probabilistic Relational Databases.
Proceedings of the Web-Age Information Management - 15th International Conference, 2014

Get a Sample for a Discount - Sampling-Based XML Data Pricing.
Proceedings of the Database and Expert Systems Applications, 2014

Conditioning Probabilistic Relational Data with Referential Constraints.
Proceedings of the Database Systems for Advanced Applications, 2014

Integration of Web Sources Under Uncertainty and Dependencies Using Probabilistic XML.
Proceedings of the Database Systems for Advanced Applications, 2014

2013
The Price Is Right - Models and Algorithms for Pricing Data.
Proceedings of the Database and Expert Systems Applications, 2013

What You Pay for Is What You Get.
Proceedings of the Database and Expert Systems Applications, 2013

Querying Semi-structured Data with Mutual Exclusion.
Proceedings of the Database Systems for Advanced Applications, 2013

2012
A Hybrid Approach for General XML Query Processing.
Proceedings of the Database and Expert Systems Applications, 2012

A Framework for Conditioning Uncertain Relational Data.
Proceedings of the Database and Expert Systems Applications, 2012

2011
Measuring XML Structured-ness with Entropy.
Proceedings of the Web-Age Information Management, 2011

Edit Distance between XML and Probabilistic XML Documents.
Proceedings of the Database and Expert Systems Applications, 2011


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