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Intermittent-Aware Neural Architecture Search
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-58526-6_39openalex-snapshot
Neural Predictor for Neural Architecture Search
inferredcites →https://doi.org/10.1007/s11265-007-0085-2openalex-snapshot
Calibration of Abstract Performance Models for System-Level Design Space Exploration
inferredcites →https://doi.org/10.1016/j.sysarc.2020.101859openalex-snapshot
A survey of techniques for intermittent computing
inferredcites →https://doi.org/10.1109/asap.2018.8445101openalex-snapshot
GAP-8: A RISC-V SoC for AI at the Edge of the IoT
inferredcites →https://doi.org/10.1109/cvpr.2015.7299173openalex-snapshot
Convolutional neural networks at constrained time cost
inferredcites →https://doi.org/10.1109/cvpr.2019.00293openalex-snapshot
MnasNet: Platform-Aware Neural Architecture Search for Mobile
inferredcites →https://doi.org/10.1109/cvpr.2019.01099openalex-snapshot
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00215openalex-snapshot
APQ: Joint Search for Network Architecture, Pruning and Quantization Policy
inferredcites →https://doi.org/10.1109/dac18072.2020.9218526openalex-snapshot
Intermittent Inference with Nonuniformly Compressed Multi-Exit Neural Network for Energy Harvesting Powered Devices
inferredcites →https://doi.org/10.1109/dac18072.2020.9218596openalex-snapshot
Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator
inferredcites →https://doi.org/10.1109/dac18072.2020.9218676openalex-snapshot
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks
inferredcites →https://doi.org/10.1109/dac18072.2020.9218749openalex-snapshot
EDD: Efficient Differentiable DNN Architecture and Implementation Co-search for Embedded AI Solutions
inferredcites →https://doi.org/10.1109/dac18074.2021.9586121openalex-snapshot
DANCE: Differentiable Accelerator/Network Co-Exploration
inferredcites →https://doi.org/10.1109/hpca.2015.7056060openalex-snapshot
Architecture exploration for ambient energy harvesting nonvolatile processors
inferredcites →https://doi.org/10.1109/iccad45719.2019.8942147openalex-snapshot
Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning
inferredcites →https://doi.org/10.1109/iscas51556.2021.9401799openalex-snapshot
Developing a Miniature Energy-Harvesting-Powered Edge Device with Multi-Exit Neural Network
inferredcites →https://doi.org/10.1109/jproc.2017.2761740openalex-snapshot
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
inferredcites →https://doi.org/10.1109/jssc.2016.2616357openalex-snapshot
Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/mm.2015.88openalex-snapshot
Nonvolatile Processor Architecture Exploration for Energy-Harvesting Applications
inferredcites →https://doi.org/10.1109/rtas48715.2020.00-14openalex-snapshot
Scheduling Computational and Energy Harvesting Tasks in Deadline-Aware Intermittent Systems
inferredcites →https://doi.org/10.1109/tcad.2020.2986127openalex-snapshot
Hardware/Software Co-Exploration of Neural Architectures
inferredcites →https://doi.org/10.1109/tcad.2020.3012217openalex-snapshot
Everything Leaves Footprints: Hardware Accelerated Intermittent Deep Inference
inferredcites →https://doi.org/10.1109/tcad.2020.3012863openalex-snapshot
Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search With Hot Start
inferredcites →https://doi.org/10.1109/tcad.2021.3059561openalex-snapshot
State-of-Charge Estimation of Supercapacitors in Transiently-Powered Sensor Nodes
inferredcites →https://doi.org/10.1109/tcad.2021.3066563openalex-snapshot
An Efficient Hardware Design for Accelerating Sparse CNNs With NAS-Based Models
inferredcites →https://doi.org/10.1109/tvlsi.2018.2815603openalex-snapshot
Optimizing the Convolution Operation to Accelerate Deep Neural Networks on FPGA
inferredcites →https://doi.org/10.1145/1347375.1347389openalex-snapshot
The worst-case execution-time problem—overview of methods and survey of tools
inferredcites →https://doi.org/10.1145/2684746.2689060openalex-snapshot
Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1145/2983628openalex-snapshot
Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in Intermittently-Powered IoT Devices
inferredcites →https://doi.org/10.1145/3037697.3037711openalex-snapshot
Determining Application-specific Peak Power and Energy Requirements for Ultra-low Power Processors
inferredcites →https://doi.org/10.1145/3079856.3080221openalex-snapshot
Maximizing CNN Accelerator Efficiency Through Resource Partitioning
inferredcites →https://doi.org/10.1145/3093337.3037711openalex-snapshot
Determining Application-specific Peak Power and Energy Requirements for Ultra-low Power Processors
inferredcites →https://doi.org/10.1145/3131672.3131699openalex-snapshot
The Future of Sensing is Batteryless, Intermittent, and Awesome
inferredcites →https://doi.org/10.1145/3133920openalex-snapshot
Alpaca: intermittent execution without checkpoints
inferredcites →https://doi.org/10.1145/3140659.3080221openalex-snapshot
Maximizing CNN Accelerator Efficiency Through Resource Partitioning
inferredcites →https://doi.org/10.1145/3173162.3173210openalex-snapshot
A Reconfigurable Energy Storage Architecture for Energy-harvesting Devices
inferredcites →https://doi.org/10.1145/3279755.3279759openalex-snapshot
Enabling intermittent computing on high-performance out-of-order processors
inferredcites →https://doi.org/10.1145/3296957.3173210openalex-snapshot
A Reconfigurable Energy Storage Architecture for Energy-harvesting Devices
inferredcites →https://doi.org/10.1145/3310273.3323435openalex-snapshot
Optimization and deployment of CNNs at the edge
inferredcites →https://doi.org/10.1145/3371392openalex-snapshot
Low Overhead Online Data Flow Tracking for Intermittently Powered Non-Volatile FPGAs
inferredcites →https://doi.org/10.1145/3377930.3389834openalex-snapshot
An evolutionary optimization algorithm for gradually saturating objective functions
inferredcites →https://doi.org/10.1145/3391893openalex-snapshot
Demystifying Energy Consumption Dynamics in Transiently powered Computers
inferredcites →https://doi.org/10.1145/3458473.3458822openalex-snapshot
Automatic energy model generation with MSP430 EnergyTrace
inferredcites →https://doi.org/10.23919/date.2018.8342033openalex-snapshot
SmartShuttle: Optimizing off-chip memory accesses for deep learning accelerators
inferredcites →https://doi.org/10.48550/arxiv.1802.05668openalex-snapshot
Model compression via distillation and quantization
inferredcites →https://doi.org/10.48550/arxiv.1808.05377openalex-snapshot
Neural Architecture Search: A Survey
inferredcites →https://doi.org/10.48550/arxiv.1911.00105openalex-snapshot
On Neural Architecture Search for Resource-Constrained Hardware Platforms
inferredcites →https://doi.org/10.48550/arxiv.2007.10319openalex-snapshot
MCUNet: Tiny Deep Learning on IoT Devices
inferredcites →https://doi.org/10.57702/zp44cu3gopenalex-snapshot
Learning Multiple Layers of Features from Tiny Images
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4782177openalex-extracted
Interaxnn: A Reconfigurable and Approximate In-Memory Processing Accelerator for Ultra-Low-Power Binary Neural Network Inference in Intermittently Powered Systems
inferred← citeshttps://doi.org/10.1007/s10462-024-11058-wopenalex-snapshot
Systematic review on neural architecture search
inferred← citeshttps://doi.org/10.1016/j.sysarc.2022.102743openalex-snapshot
Transient computing for energy harvesting systems: A survey
inferred← citeshttps://doi.org/10.1109/access.2022.3203719openalex-snapshot
Efficient DNN Execution on Intermittently-Powered IoT Devices With Depth-First Inference
inferred← citeshttps://doi.org/10.1109/access.2022.3225092openalex-snapshot
Deep Learning on Energy Harvesting IoT Devices: Survey and Future Challenges
inferred← citeshttps://doi.org/10.1109/access.2024.3365349openalex-snapshot
A Machine Learning-Oriented Survey on Tiny Machine Learning
inferred← citeshttps://doi.org/10.1109/dac56929.2023.10247825openalex-snapshot
Intermittent-Aware Neural Network Pruning
inferred← citeshttps://doi.org/10.1109/hpca57654.2024.00073openalex-snapshot
Usas: A Sustainable Continuous-Learning´ Framework for Edge Servers
inferred← citeshttps://doi.org/10.1109/icbdml68582.2026.11544178openalex-snapshot
Energy-Aware Deep Neural Networks for Resource-Constrained Devices
inferred← citeshttps://doi.org/10.1109/iccad57390.2023.10323634openalex-snapshot
TRAIN: A Reinforcement Learning Based Timing-Aware Neural Inference on Intermittent Systems
inferred← citeshttps://doi.org/10.1109/icites56274.2022.9943754openalex-snapshot
Memory Layout Optimization for Task-Based Intermittent Computing Systems
inferred← citeshttps://doi.org/10.1109/ipccc59868.2024.10850328openalex-snapshot
HANNA: Harvesting-Aware Neural Network Architecture Search for Batteryless Intermittent Devices
inferred← citeshttps://doi.org/10.1109/isca59077.2024.00022openalex-snapshot
A Tale of Two Domains: Exploring Efficient Architecture Design for Truly Autonomous Things
inferred← citeshttps://doi.org/10.1109/isqed65160.2025.11014335openalex-snapshot
Energy-Adaptive Checkpoint-Free Intermittent Inference for Low Power Energy Harvesting Systems
inferred← citeshttps://doi.org/10.1109/jsen.2022.3210773openalex-snapshot
Machine Learning for Microcontroller-Class Hardware: A Review
inferred← citeshttps://doi.org/10.1109/rtas54340.2022.00012openalex-snapshot
Compiler-Directed High-Performance Intermittent Computation with Power Failure Immunity
inferred← citeshttps://doi.org/10.1109/tcad.2022.3197513openalex-snapshot
Stateful Neural Networks for Intermittent Systems
inferred← citeshttps://doi.org/10.1109/tcad.2022.3202861openalex-snapshot
CapOS: Capacitor Error Resilience for Energy Harvesting Systems
inferred← citeshttps://doi.org/10.1109/tcad.2024.3443698openalex-snapshot
iFKVS: Lightweight Key-Value Store for Flash-Based Intermittently Computing Devices
inferred← citeshttps://doi.org/10.1109/tcad.2024.3443710openalex-snapshot
MII: A Multifaceted Framework for Intermittence-Aware Inference and Scheduling
inferred← citeshttps://doi.org/10.1109/tcad.2025.3555963openalex-snapshot
Intermittent-Friendly Neural Architecture Search: Demystifying Accuracy and Overhead Tradeoffs
inferred← citeshttps://doi.org/10.1109/tetc.2025.3643888openalex-snapshot
CARTOS: A Charging-Aware Real-Time Operating System for Intermittent Batteryless Devices
inferred← citeshttps://doi.org/10.1145/3524500openalex-snapshot
Neural Architecture Search Survey: A Hardware Perspective
inferred← citeshttps://doi.org/10.1145/3546193openalex-snapshot
Experimental Demonstration of STT-MRAM-based Nonvolatile Instantly On/Off System for IoT Applications: Case Studies
inferred← citeshttps://doi.org/10.1145/3603171openalex-snapshot
TinyNS: Platform-aware Neurosymbolic Auto Tiny Machine Learning
inferred← citeshttps://doi.org/10.1145/3607918openalex-snapshot
Keep in Balance: Runtime-reconfigurable Intermittent Deep Inference
inferred← citeshttps://doi.org/10.1145/3626197openalex-snapshot
Energy-Efficient Communications for Improving Timely Progress of Intermittent-Powered BLE Devices
inferred← citeshttps://doi.org/10.1145/3649476.3658798openalex-snapshot
Autotile: Autonomous Task-tiling for Deep Inference on Battery-less Embedded System
inferred← citeshttps://doi.org/10.1145/3666025.3699364openalex-snapshot
Intermittent Inference: Trading a 1% Accuracy Loss for a 1.9x Throughput Speedup
inferred← citeshttps://doi.org/10.1145/3715014.3722059openalex-snapshot
Lupe: Integrating the Top-down Approach with DNN Execution on Ultra-Low-Power Devices
inferred← citeshttps://doi.org/10.1145/3748522.3779848openalex-snapshot
A Volunteer Computing Framework for IoT Devices using Intermittent Computing
inferred← citeshttps://doi.org/10.1145/3757917openalex-snapshot
Catch Non-determinism If You Can: Intermittent Inference of Dynamic Neural Networks
inferred← citeshttps://doi.org/10.1145/3771845openalex-snapshot
InterAxNN: Reconfigurable and Approximate in-Memory Processing Accelerator for Ultra-Low-Power Binary Neural Network Inference in Intermittently Powered Systems
inferred← citeshttps://doi.org/10.1145/3774906.3802781openalex-snapshot
ConvReflex: Efficient Ultra-Low-Power CNN Inference via Clamping Prediction
inferred← citeshttps://doi.org/10.1145/3814956openalex-snapshot
Timing-Constrained Composable Inference for Intermittent Systems Using Reinforcement Learning
inferred← citeshttps://doi.org/10.1145/3816440.3818584openalex-snapshot
GECKO: Graph-Evolving aware C hec K p O inter for Intermittent Systems
inferred← citeshttps://doi.org/10.1145/3856824openalex-snapshot
CAMEO: Compressive Energy-Aware Multi-Task Deep Inference in Resource-Constrained Energy Harvesting Systems
inferred← citeshttps://doi.org/10.1287/ijoc.2023.0034openalex-snapshot
An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development
inferred← citeshttps://doi.org/10.23919/date54114.2022.9774756openalex-snapshot
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices
inferred← citeshttps://doi.org/10.32388/izohchopenalex-snapshot
Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies
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Artificial Intelligence for Energy Processes and Systems: Applications and Perspectives
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