On the public citation graph

Achieving Lossless Accuracy with Lossy Programming for Efficient Neural-Network Training on NVM-Based Systems

https://doi.org/10.1145/3358191
0 signed · 51 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_32openalex-snapshot
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot
ImageNet Large Scale Visual Recognition Challenge
inferredcites →https://doi.org/10.1007/s11263-020-01316-zopenalex-snapshot
The Open Images Dataset V4
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvpr31182.2015openalex-snapshot
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
inferredcites →https://doi.org/10.1109/fpl32523.2014openalex-snapshot
2014 24th International Conference on Field Programmable Logic and Applications (FPL)
inferredcites →https://doi.org/10.1109/hpca32246.2014openalex-snapshot
2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA)
inferredcites →https://doi.org/10.1109/iccad51958.2021openalex-snapshot
2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)
inferredcites →https://doi.org/10.1109/iccd41353.2017openalex-snapshot
2017 IEEE International Conference on Computer Design (ICCD)
inferredcites →https://doi.org/10.1109/imw59701.2024openalex-snapshot
2024 IEEE International Memory Workshop (IMW)
inferredcites →https://doi.org/10.1109/isca36197.2016openalex-snapshot
2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA)
inferredcites →https://doi.org/10.1109/led.2009.2037183openalex-snapshot
2010 IEEE Symposium on VLSI Technology
inferredcites →https://doi.org/10.1109/micro.2016.7783721openalex-snapshot
vDNN: Virtualized deep neural networks for scalable, memory-efficient neural network design
inferredcites →https://doi.org/10.1109/micro37956.2016openalex-snapshot
2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)
inferredcites →https://doi.org/10.1109/nvmsa47269.2019openalex-snapshot
2019 IEEE Non-Volatile Memory Systems and Applications Symposium (NVMSA)
inferredcites →https://doi.org/10.1109/tcad.2018.2858360openalex-snapshot
Power- and Endurance-Aware Neural Network Training in NVM-Based Platforms
inferredcites →https://doi.org/10.1109/tcad.2018.2858459openalex-snapshot
Hot-Spot Suppression for Resource-Constrained Image Recognition Devices With Nonvolatile Memory
inferredcites →https://doi.org/10.1109/ted.2007.914505openalex-snapshot
2008 Symposium on VLSI Technology
inferredcites →https://doi.org/10.1109/tvlsi.2018.2819210openalex-snapshot
Boosting NVDIMM Performance With a Lightweight Caching Algorithm
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1145/139669openalex-snapshot
Proceedings of the 19th annual international symposium on Computer architecture - ISCA '92
inferredcites →https://doi.org/10.1145/1555754.1555759openalex-snapshot
A durable and energy efficient main memory using phase change memory technology
inferredcites →https://doi.org/10.1145/1555815.1555758openalex-snapshot
Architecting phase change memory as a scalable dram alternative
inferredcites →https://doi.org/10.1145/2366231.2337203openalex-snapshot
PreSET
inferredcites →https://doi.org/10.1145/775832openalex-snapshot
Proceedings of the 40th annual Design Automation Conference
inferredcites →https://doi.org/10.48550/arxiv.1404.5997openalex-snapshot
One weird trick for parallelizing convolutional neural networks
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1502.02551openalex-snapshot
Deep Learning with Limited Numerical Precision
inferredcites →https://doi.org/10.48550/arxiv.1511.00363openalex-snapshot
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
inferredcites →https://doi.org/10.48550/arxiv.1602.07360openalex-snapshot
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
inferredcites →https://doi.org/10.48550/arxiv.1604.03168openalex-snapshot
Hardware-oriented Approximation of Convolutional Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1704.04861openalex-snapshot
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1109/euc53437.2021.00010openalex-snapshot
scList: A PCRAM-based Hybrid Memory Management Scheme
inferred← citeshttps://doi.org/10.1109/icassp43922.2022.9747219openalex-snapshot
Speech Recovery For Real-World Self-Powered Intermittent Devices
inferred← citeshttps://doi.org/10.1109/les.2023.3298742openalex-snapshot
Swift-CNN: Leveraging PCM Memory’s Fast Write Mode to Accelerate CNNs
inferred← citeshttps://doi.org/10.1109/nvmsa53655.2021.9628582openalex-snapshot
Approximate Programming Design for Enhancing Energy, Endurance and Performance of Neural Network Training on NVM-based Systems
inferred← citeshttps://doi.org/10.1109/tcad.2020.3012250openalex-snapshot
On Minimizing Analog Variation Errors to Resolve the Scalability Issue of ReRAM-Based Crossbar Accelerators
inferred← citeshttps://doi.org/10.1109/tcad.2021.3097298openalex-snapshot
Leveraging Write Heterogeneity of Phase Change Memory on Supporting Self-Balancing Binary Tree
inferred← citeshttps://doi.org/10.1109/tcad.2022.3204231openalex-snapshot
Energy Efficiency Enhancement of SCM-Based Systems: Write-Friendly Coding
inferred← citeshttps://doi.org/10.1109/tcad.2023.3241563openalex-snapshot
DTC: A Drift-Tolerant Coding to Improve the Performance and Energy Efficiency of -Level-Cell Phase-Change Memory
inferred← citeshttps://doi.org/10.1109/tpds.2022.3193867openalex-snapshot
Accelerating Tensor Swapping in GPUs With Self-Tuning Compression
inferred← citeshttps://doi.org/10.1109/tsusc.2025.3526241openalex-snapshot
Synapse: Synergizing Approximate STT-MRAM and CNN Features for Energy-Efficient Accelerators
inferred← citeshttps://doi.org/10.1145/3394885.3431511openalex-snapshot
A Write-friendly Arithmetic Coding Scheme for Achieving Energy-Efficient Non-Volatile Memory Systems
inferred← citeshttps://doi.org/10.1145/3477314.3507090openalex-snapshot
RAM
inferred← citeshttps://doi.org/10.1145/3508352.3549408openalex-snapshot
GraphRC
inferred← citeshttps://doi.org/10.1145/3531437.3539701openalex-snapshot
Drift-tolerant Coding to Enhance the Energy Efficiency of Multi-Level-Cell Phase-Change Memory
inferred← citeshttps://doi.org/10.1145/3607889openalex-snapshot
Proceedings of the International Conference on Compilers, Architecture, and Synthesis for Embedded Systems
inferred← citeshttps://doi.org/10.1145/3607889.3609088openalex-snapshot
Special Session - Non-Volatile Memories: Challenges and Opportunities for Embedded System Architectures with Focus on Machine Learning Applications
inferred← citeshttps://doi.org/10.1145/3670404openalex-snapshot
Estimating Power, Performance, and Area for On-Sensor Deployment of AR/VR Workloads Using an Analytical Framework
inferred← citeshttps://doi.org/10.1145/3676536.3697115openalex-snapshot
Non-volatile Memory Technologies for Edge AI Applications
inferred← citeshttps://doi.org/10.23919/date51398.2021.9474229openalex-snapshot
Future Computing Platform Design: A Cross-Layer Design Approach
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.