Wenlin Chen

This page is a disambiguation page, it actually contains multiple papers from persons of the same or a similar name.

Bibliography

2026
LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation.
CoRR, May, 2026

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale.
CoRR, May, 2026

SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling.
CoRR, April, 2026

Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design.
CoRR, February, 2026

Generative Reasoning Re-ranker.
CoRR, February, 2026


2025
Confucius Code Agent: Scalable Agent Scaffolding for Real-World Codebases.
CoRR, December, 2025

Meta Lattice: Model Space Redesign for Cost-Effective Industry-Scale Ads Recommendations.
CoRR, December, 2025

BridgeDrive: Diffusion Bridge Policy for Closed-Loop Trajectory Planning in Autonomous Driving.
CoRR, September, 2025

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation.
CoRR, February, 2025

Towards Training One-Step Diffusion Models Without Distillation.
CoRR, February, 2025

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Progressive Tempering Sampler with Diffusion.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

Training Neural Samplers with Reverse Diffusive KL Divergence.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024
Leveraging Task Structures for Improved Identifiability in Neural Network Representations.
Trans. Mach. Learn. Res., 2024

Pride or Guilt? Impacts of Consumers' Socially Influenced Recycling Behaviors on Closed-Loop Supply Chains.
Manuf. Serv. Oper. Manag., 2024

Your Image is Secretly the Last Frame of a Pseudo Video.
CoRR, 2024

Wukong: Towards a Scaling Law for Large-Scale Recommendation.
CoRR, 2024

Research on Explainability Methods for Unmanned Combat Decision-Making Models.
IEEE Access, 2024

Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

The Effect of AI-delivered Patient Education on Patients' Willingness to Participate in Hand Hygiene: The Mediating Role of Role Stress.
Proceedings of the 2024 7th International Conference on Information Management and Management Science, 2024

Wukong: Towards a Scaling Law for Large-Scale Recommendation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Diffusive Gibbs Sampling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Modelling Variability in Human Annotator Simulation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
It HAS to be Subjective: Human Annotator Simulation via Zero-shot Density Estimation.
CoRR, 2023

Neural Characteristic Activation Value Analysis for Improved ReLU Network Feature Learning.
CoRR, 2023

Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Research on the impact of influencers on audiences' intention to follow.
Proceedings of the 14th International Conference on E-business, Management and Economics, 2023

Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking.
Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023

2022
Optimal Client Sampling for Federated Learning.
Trans. Mach. Learn. Res., 2022

A Homomorphism Transform Based Analysis of Sparse Random Linear Network Coding Over Erasure Channels.
IEEE Commun. Lett., 2022

2021
A Decision-Making Framework of Hybrid System Based on Modified Hybrid Stochastic Timed Petri Net and Deep Learning.
IEEE Syst. J., 2021

Improved Expression for Rank Distribution of Sparse Random Linear Network Coding.
IEEE Commun. Lett., 2021

Exact Decoding Probability of Sparse Random Linear Network Coding for Reliable Multicast.
CoRR, 2021

Experimental Study on Dynamic Characteristics and Fatigue of McKibben Pneumatic Artificial Muscles.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2021

Information Design to Motivate Users to Comply With Barrage Etiquette on Video Website: Evidence from a Discrete Choice Experiment.
Proceedings of the IMMS 2021: 4th International Conference on Information Management and Management Science, Chengdu, China, August 27, 2021

2020
Improving Hand Hygiene Process Compliance Through Process Monitoring in Healthcare.
Manuf. Serv. Oper. Manag., 2020

The Decoding Success Probability of Sparse Random Linear Network Coding for Multicast.
CoRR, 2020

Stiffness Analysis of a Pneumatic Soft Manipulator Based on Bending Shape Prediction.
IEEE Access, 2020

To Ensemble or Not Ensemble: When Does End-to-End Training Fail?
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

2019
Deep Learning Recommendation Model for Personalization and Recommendation Systems.
CoRR, 2019

The Rank Distribution of Sparse Random Linear Network Coding.
IEEE Access, 2019

Nonlinear identification of IPMC actuators employing RFNN-NARX model and Particle Swarm Optimization.
Proceedings of the 2019 IEEE International Conference on Robotics and Biomimetics, 2019

2016
Multi-Scale Convolutional Neural Networks for Time Series Classification.
CoRR, 2016

Deep Metric Learning with Data Summarization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Compressing Convolutional Neural Networks in the Frequency Domain.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Strategies for Training Large Vocabulary Neural Language Models.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015
Nonlinear Metric Learning with Kernel Density Estimation.
IEEE Trans. Knowl. Data Eng., 2015

Compressing Convolutional Neural Networks.
CoRR, 2015

A unifying learning framework for building artificial game-playing agents.
Ann. Math. Artif. Intell., 2015

Fast Distributed k-Center Clustering with Outliers on Massive Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimal Action Extraction for Random Forests and Boosted Trees.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Compressing Neural Networks with the Hashing Trick.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Mortality Prediction in ICUs Using A Novel Time-Slicing Cox Regression Method.
Proceedings of the AMIA 2015, 2015

Filtered Search for Submodular Maximization with Controllable Approximation Bounds.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Fast flux discriminant for large-scale sparse nonlinear classification.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Feature-Cost Sensitive Learning with Submodular Trees of Classifiers.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Density-based logistic regression.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Maximum Variance Correction with Application to A* Search.
Proceedings of the 30th International Conference on Machine Learning, 2013

Kernel Density Metric Learning.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Utilizing Landmarks in Euclidean Heuristics for Optimal Planning.
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013

Goal-Oriented Euclidean Heuristics with Manifold Learning.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
An integrated data mining approach to real-time clinical monitoring and deterioration warning.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012


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