Jiyan Yang

Orcid: 0009-0005-5946-5456

According to our database1, Jiyan Yang authored at least 32 papers between 2014 and 2023.

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Bibliography

2023
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale.
CoRR, 2023

AutoML for Large Capacity Modeling of Meta's Ranking Systems.
CoRR, 2023

AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 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


2021
High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.
CoRR, 2021

Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery.
Proceedings of Machine Learning and Systems 2021, 2021

Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems.
Proceedings of the IEEE International Symposium on Information Theory, 2021

2020
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery.
CoRR, 2020

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data.
CoRR, 2020

Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems.
CoRR, 2020

ShadowSync: Performing Synchronization in the Background for Highly Scalable Distributed Training.
CoRR, 2020

Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
Post-Training 4-bit Quantization on Embedding Tables.
CoRR, 2019

A Study of BFLOAT16 for Deep Learning Training.
CoRR, 2019

2017
Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning.
J. Mach. Learn. Res., 2017

2016
Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty.
IEEE Trans. Smart Grid, 2016

Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments.
Proc. IEEE, 2016

Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels.
J. Mach. Learn. Res., 2016

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
CoRR, 2016

Weighted SGD for <i>ℓ<sub>p</sub></i> Regression with Randomized Preconditioning.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Feature-distributed sparse regression: a screen-and-clean approach.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Sub-sampled Newton Methods with Non-uniform Sampling.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Tensor machines for learning target-specific polynomial features.
CoRR, 2015

2014
Quantile Regression for Large-Scale Applications.
SIAM J. Sci. Comput., 2014

Modeling and online control of generalized energy storage networks.
Proceedings of the Fifth International Conference on Future Energy Systems, 2014

Random Laplace Feature Maps for Semigroup Kernels on Histograms.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014


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