Ellie Wen
Orcid: 0000-0001-8229-2294
According to our database1,
Ellie Wen
authored at least 15 papers
between 2020 and 2025.
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Bibliography
2025
External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation.
CoRR, February, 2025
Personalized Interpolation: An Efficient Method to Tame Flexible Optimization Window Estimation.
CoRR, January, 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
Negative Exclusion Filtering: Optimizing Ad Delivery Efficiency for Large-Scale Social Media Platforms.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
2024
QuickUpdate: a Real-Time Personalization System for Large-Scale Recommendation Models.
Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024
Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large Scale Recommendation.
Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 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
DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction.
CoRR, 2022
Software-hardware co-design for fast and scalable training of deep learning recommendation models.
Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022
2021
IEEE Micro, 2021
High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.
CoRR, 2021
2020
Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data.
CoRR, 2020