Sotabase

Career

· Senior Tech Lead Manager, Meta2021–
· Research Scientist, Meta2016–2021
· Modeling Analytics Intern, JPMorgan Chase & Co.2015–2015
· Research Intern, eBay Research Labs2014–2014
· Research Intern, IBM T.J. Watson Research Center2013–2013
· Research Collaborator, Lawrence Berkeley National Laboratory2013–2015
· Research Assistant, Stanford University2012–2016
· Teaching Assistant, Stanford University2012–2012
· Doctor of Philosophy (Ph.D.), Computational Mathematics, Stanford University2011–2016
· Bachelor of Science (B.S.), Mathematics, Nanjing University2007–2011

Publications (38)

A Study of BFLOAT16 for Deep Learning Training
arXiv.org · 2019
434
cited
Software-hardware co-design for fast and scalable training of deep learning recommendation models
International Symposium on Computer Architecture · 2021
178
cited
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Journal of machine learning research · 2014
173
cited
Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems
Knowledge Discovery and Data Mining · 2019
135
cited
Sub-sampled Newton Methods with Non-uniform Sampling
Neural Information Processing Systems · 2016
122
cited
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems
International Symposium on Information Theory · 2019
108
cited
Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems
arXiv.org · 2020
103
cited
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction
Knowledge Discovery and Data Mining · 2020
89
cited
Online Modified Greedy algorithm for storage control under uncertainty
IEEE Power & Energy Society General Meeting · 2014
63
cited
Quantile Regression for Large-Scale Applications
SIAM Journal on Scientific Computing · 2013
63
cited
Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments
Proceedings of the IEEE · 2015
60
cited
Random Laplace Feature Maps for Semigroup Kernels on Histograms
2014 IEEE Conference on Computer Vision and Pattern Recognition · 2014
53
cited
2016 Ieee International Conference on Big Data (big Data) Matrix Factorizations at Scale: a Comparison of Scientific Data Analytics in Spark and C+mpi Using Three Case Studies
50
cited
High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models
arXiv.org · 2021
46
cited
Post-Training 4-bit Quantization on Embedding Tables
arXiv.org · 2019
45
cited
Weighted SGD for ℓp Regression with Randomized Preconditioning
ACM-SIAM Symposium on Discrete Algorithms · 2015
43
cited
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery
Conference on Machine Learning and Systems · 2020
41
cited
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies
arXiv.org · 2016
39
cited
Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty
IEEE Transactions on Smart Grid · 2014
38
cited
Identifying important ions and positions in mass spectrometry imaging data using CUR matrix decompositions.
Analytical Chemistry · 2015
36
cited
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Jiyan Yang | Researcher Profile | Sotabase | Sotabase