Feng Yan

Orcid: 0000-0001-9840-7754

Affiliations:
  • University of Houston, Department of Computer Science, Houston, TX, USA
  • University of Nevada, Department of Computer Science and Engineering, Reno, USA (former)
  • College of William and Mary, Williamsburg, VA, USA (former, PhD 2016)


According to our database1, Feng Yan authored at least 106 papers between 2011 and 2024.

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

Timeline

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Bibliography

2024
MalleTrain: Deep Neural Network Training on Unfillable Supercomputer Nodes.
CoRR, 2024

Peeking Behind the Curtains of Residual Learning.
CoRR, 2024

MalleTrain: Deep Neural Networks Training on Unfillable Supercomputer Nodes.
Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

ZeRO++: Extremely Efficient Collective Communication for Large Model Training.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning.
Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024

Noctua: Towards Automated and Practical Fine-grained Consistency Analysis.
Proceedings of the Nineteenth European Conference on Computer Systems, 2024

CSCO: Connectivity Search of Convolutional Operators.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
AI augmented Edge and Fog computing: Trends and challenges.
J. Netw. Comput. Appl., July, 2023

InfiniStore: Elastic Serverless Cloud Storage.
Proc. VLDB Endow., 2023

Speed Up Federated Learning in Heterogeneous Environment: A Dynamic Tiering Approach.
CoRR, 2023

DistDNAS: Search Efficient Feature Interactions within 2 Hours.
CoRR, 2023

Farthest Greedy Path Sampling for Two-shot Recommender Search.
CoRR, 2023

ZeRO++: Extremely Efficient Collective Communication for Giant Model Training.
CoRR, 2023

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems.
Proceedings of the ACM Web Conference 2023, 2023

: Joint Point Interaction-Dimension Search for 3D Point Cloud.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

DySR: Adaptive Super-Resolution via Algorithm and System Co-design.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

MPress: Democratizing Billion-Scale Model Training on Multi-GPU Servers via Memory-Saving Inter-Operator Parallelism.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023

SciLance: Mitigate Load Imbalance for Parallel Scientific Applications in Cloud Environments.
Proceedings of the IEEE International Conference on Cluster Computing, 2023

HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2022
Enabling Cost-Effective, SLO-Aware Machine Learning Inference Serving on Public Cloud.
IEEE Trans. Cloud Comput., 2022

Memory Scaling of Cloud-Based Big Data Systems: A Hybrid Approach.
IEEE Trans. Big Data, 2022

Nemo: An Open-Source Transformer-Supercharged Benchmark for Fine-Grained Wildfire Smoke Detection.
Remote. Sens., 2022

Optimizing Inference Serving on Serverless Platforms.
Proc. VLDB Endow., 2022

PIDS: Joint Point Interaction-Dimension Search for 3D Point Cloud.
CoRR, 2022

Sion: Elastic Serverless Cloud Storage.
CoRR, 2022

BiFeat: Supercharge GNN Training via Graph Feature Quantization.
CoRR, 2022

SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training.
CoRR, 2022

Topological Modeling and Parallelization of Multidimensional Data on Microelectrode Arrays.
Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

Heterogeneity-Aware Adaptive Federated Learning Scheduling.
Proceedings of the IEEE International Conference on Big Data, 2022

ScaleNAS: Multi-Path One-Shot NAS for Scale-Aware High-Resolution Representation.
Proceedings of the International Conference on Automated Machine Learning, 2022

TIFF: Tokenized Incentive for Federated Learning.
Proceedings of the IEEE 15th International Conference on Cloud Computing, 2022

Systems Bias in Federated Learning.
Proceedings of the Federated Learning, 2022

Straggler Management.
Proceedings of the Federated Learning, 2022

Local Training and Scalability of Federated Learning Systems.
Proceedings of the Federated Learning, 2022

Introduction to Federated Learning Systems.
Proceedings of the Federated Learning, 2022

2021
CEDULE+: Resource Management for Burstable Cloud Instances Using Predictive Analytics.
IEEE Trans. Netw. Serv. Manag., 2021

STEP: A Spatio-Temporal Fine-Granular User Traffic Prediction System for Cellular Networks.
IEEE Trans. Mob. Comput., 2021

AutoGR: Automated Geo-Replication with Fast System Performance and Preserved Application Semantics.
Proc. VLDB Endow., 2021

Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX.
CoRR, 2021

Gradient Compression Supercharged High-Performance Data Parallel DNN Training.
Proceedings of the SOSP '21: ACM SIGOPS 28th Symposium on Operating Systems Principles, 2021

Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression.
Proceedings of the 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data, 2021

Lunule: an agile and judicious metadata load balancer for CephFS.
Proceedings of the International Conference for High Performance Computing, 2021

BAASH: lightweight, efficient, and reliable blockchain-as-a-service for HPC systems.
Proceedings of the International Conference for High Performance Computing, 2021

X-composer: enabling cross-environments in-situ workflows between HPC and cloud.
Proceedings of the PASC '21: Platform for Advanced Scientific Computing Conference, 2021

SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Age of Correlated Features in Supervised Learning based Forecasting.
Proceedings of the 2021 IEEE Conference on Computer Communications Workshops, 2021

SciChain: Blockchain-enabled Lightweight and Efficient Data Provenance for Reproducible Scientific Computing.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning.
Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

NASGEM: Neural Architecture Search via Graph Embedding Method.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Reinforcement-Learning-Empowered MLaaS Scheduling for Serving Intelligent Internet of Things.
IEEE Internet Things J., 2020

ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition.
CoRR, 2020

ElasticBroker: Combining HPC with Cloud to Provide Realtime Insights into Simulations.
CoRR, 2020

NASGEM: Neural Architecture Search via Graph Embedding Method.
CoRR, 2020

Distributed Nonblocking Commit Protocols for Many-Party Cross-Blockchain Transactions.
CoRR, 2020

BatchCrypt: Efficient Homomorphic Encryption for Cross-Silo Federated Learning.
Proceedings of the 2020 USENIX Annual Technical Conference, 2020

SEFEE: lightweight storage error forecasting in large-scale enterprise storage systems.
Proceedings of the International Conference for High Performance Computing, 2020

Batch: machine learning inference serving on serverless platforms with adaptive batching.
Proceedings of the International Conference for High Performance Computing, 2020

AutoGrow: Automatic Layer Growing in Deep Convolutional Networks.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Not All Explorations Are Equal: Harnessing Heterogeneous Profiling Cost for Efficient MLaaS Training.
Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

TiFL: A Tier-based Federated Learning System.
Proceedings of the HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing, 2020

InfiniCache: Exploiting Ephemeral Serverless Functions to Build a Cost-Effective Memory Cache.
Proceedings of the 18th USENIX Conference on File and Storage Technologies, 2020

Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

AutoShrink: A Topology-Aware NAS for Discovering Efficient Neural Architecture.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

HDK: Toward High-Performance Deep-Learning-Based Kirchhoff Analysis.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
EPNAS: Efficient Progressive Neural Architecture Search.
CoRR, 2019

SwiftNet: Using Graph Propagation as Meta-knowledge to Search Highly Representative Neural Architectures.
CoRR, 2019

AutoGrow: Automatic Layer Growing in Deep Convolutional Networks.
CoRR, 2019

BlockLite: A Lightweight Emulator for Public Blockchains.
CoRR, 2019

MArk: Exploiting Cloud Services for Cost-Effective, SLO-Aware Machine Learning Inference Serving.
Proceedings of the 2019 USENIX Annual Technical Conference, 2019

Swift machine learning model serving scheduling: a region based reinforcement learning approach.
Proceedings of the International Conference for High Performance Computing, 2019

It's not a Sprint, it's a Marathon: Stretching Multi-resource Burstable Performance in Public Clouds.
Proceedings of the 20th International Middleware Conference Industrial Track, 2019

MSNet: Structural Wired Neural Architecture Search for Internet of Things.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

GRNN: Low-Latency and Scalable RNN Inference on GPUs.
Proceedings of the Fourteenth EuroSys Conference 2019, Dresden, Germany, March 25-28, 2019, 2019

Toward Accurate and Efficient Emulation of Public Blockchains in the Cloud.
Proceedings of the Cloud Computing - CLOUD 2019, 2019

Towards Decentralized Deep Learning with Differential Privacy.
Proceedings of the Cloud Computing - CLOUD 2019, 2019

2018
Efficient Deep Neural Network Serving: Fast and Furious.
IEEE Trans. Netw. Serv. Manag., 2018

LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning.
CoRR, 2018

Differentiable Fine-grained Quantization for Deep Neural Network Compression.
CoRR, 2018

SmoothOut: Smoothing Out Sharp Minima for Generalization in Large-Batch Deep Learning.
CoRR, 2018

Stay Fresh: Speculative Synchronization for Fast Distributed Machine Learning.
Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018

CEDULE: A Scheduling Framework for Burstable Performance in Cloud Computing.
Proceedings of the 2018 IEEE International Conference on Autonomic Computing, 2018

Toward Cost-Effective Memory Scaling in Clouds: Symbiosis of Virtual and Physical Memory.
Proceedings of the 11th IEEE International Conference on Cloud Computing, 2018

2017
DyScale: A MapReduce Job Scheduler for Heterogeneous Multicore Processors.
IEEE Trans. Cloud Comput., 2017

TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

HyperDrive: exploring hyperparameters with POP scheduling.
Proceedings of the 18th ACM/IFIP/USENIX Middleware Conference, Las Vegas, NV, USA, December 11, 2017

How to Supercharge the Amazon T2: Observations and Suggestions.
Proceedings of the 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 2017

2016
PREFiguRE: An Analytic Framework for HDD Management.
ACM Trans. Model. Perform. Evaluation Comput. Syst., 2016

Scheduling data analytics work with performance guarantees: queuing and machine learning models in synergy.
Clust. Comput., 2016

SERF: efficient scheduling for fast deep neural network serving via judicious parallelism.
Proceedings of the International Conference for High Performance Computing, 2016

Workload interleaving with performance guarantees in data centers.
Proceedings of the 2016 IEEE/IFIP Network Operations and Management Symposium, 2016

2015
PRACTISE - Demonstrating a Neural Network Based Framework for Robust Prediction of Data Center Workload.
Proceedings of the 8th IEEE/ACM International Conference on Utility and Cloud Computing, 2015

Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Proactive Management of Systems via Hybrid Analytic Techniques.
Proceedings of the 2015 International Conference on Cloud and Autonomic Computing, 2015

PRACTISE: Robust prediction of data center time series.
Proceedings of the 11th International Conference on Network and Service Management, 2015

2014
Agile middleware for scheduling: meeting competing performance requirements of diverse tasks.
Proceedings of the ACM/SPEC International Conference on Performance Engineering, 2014

Heterogeneous cores for MapReduce processing: Opportunity or challenge?
Proceedings of the 2014 IEEE Network Operations and Management Symposium, 2014

Storage Workload Isolation via Tier Warming: How Models Can Help.
Proceedings of the 11th International Conference on Autonomic Computing, 2014

Optimizing Power and Performance Trade-offs of MapReduce Job Processing with Heterogeneous Multi-core Processors.
Proceedings of the 2014 IEEE 7th International Conference on Cloud Computing, Anchorage, AK, USA, June 27, 2014

2013
Overcoming Limitations of Off-the-Shelf Priority Schedulers in Dynamic Environments.
Proceedings of the 2013 IEEE 21st International Symposium on Modelling, 2013

2012
Busy bee: how to use traffic information for better scheduling of background tasks.
Proceedings of the Third Joint WOSP/SIPEW International Conference on Performance Engineering, 2012

Quantitative Estimation of the Performance Delay with Propagation Effects in Disk Power Savings.
Proceedings of the 2012 Workshop on Power-Aware Computing Systems, HotPower'12, 2012

Fast Eventual Consistency with Performance Guarantees for Distributed Storage.
Proceedings of the 32nd International Conference on Distributed Computing Systems Workshops (ICDCS 2012 Workshops), 2012

Toward fast eventual consistency with performance guarantees.
Proceedings of the 9th International Conference on Autonomic Computing, 2012

2011
Copy rate synchronization with performance guarantees for work consolidation in storage clusters.
SIGMETRICS Perform. Evaluation Rev., 2011

Toward Automating Work Consolidation with Performance Guarantees in Storage Clusters.
Proceedings of the MASCOTS 2011, 2011


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