Once-for-All Channel Mixers (HYPERTINYPW): Generative Compression for TinyML
Fuente:
arXiv
Saved in:
| Main Author: | Shaalan, Yassien |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MLonMCU: TinyML Benchmarking with Fast Retargeting
by: van Kempen, Philipp, et al.
Published: (2023)
by: van Kempen, Philipp, et al.
Published: (2023)
TinySV: Speaker Verification in TinyML with On-device Learning
by: Pavan, Massimo, et al.
Published: (2024)
by: Pavan, Massimo, et al.
Published: (2024)
TinyML-Enabled IoT for Sustainable Precision Irrigation
by: Taueatsoala, Kamogelo, et al.
Published: (2026)
by: Taueatsoala, Kamogelo, et al.
Published: (2026)
TinyML for Acoustic Anomaly Detection in IoT Sensor Networks
by: Almaini, Amar, et al.
Published: (2026)
by: Almaini, Amar, et al.
Published: (2026)
Accelerating TinyML Inference on Microcontrollers through Approximate Kernels
by: Armeniakos, Giorgos, et al.
Published: (2024)
by: Armeniakos, Giorgos, et al.
Published: (2024)
Optimizing LoRa for Edge Computing with TinyML Pipeline for Channel Hopping
by: Grunewald, Marla, et al.
Published: (2024)
by: Grunewald, Marla, et al.
Published: (2024)
On The Dynamic Ensemble Selection for TinyML-based Systems -- a Preliminary Study
by: Puslecki, Tobiasz, et al.
Published: (2025)
by: Puslecki, Tobiasz, et al.
Published: (2025)
MicroFlow: An Efficient Rust-Based Inference Engine for TinyML
by: Carnelos, Matteo, et al.
Published: (2024)
by: Carnelos, Matteo, et al.
Published: (2024)
Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?
by: Zeinaty, Christophe El, et al.
Published: (2025)
by: Zeinaty, Christophe El, et al.
Published: (2025)
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
by: Deutel, Mark, et al.
Published: (2023)
by: Deutel, Mark, et al.
Published: (2023)
Dendron: Enhancing Human Activity Recognition with On-Device TinyML Learning
by: Shalby, Hazem Hesham Yousef, et al.
Published: (2025)
by: Shalby, Hazem Hesham Yousef, et al.
Published: (2025)
Hardware-efficient tractable probabilistic inference for TinyML Neurosymbolic AI applications
by: Leslin, Jelin, et al.
Published: (2025)
by: Leslin, Jelin, et al.
Published: (2025)
Benchmarking Energy and Latency in TinyML: A Novel Method for Resource-Constrained AI
by: Bartoli, Pietro, et al.
Published: (2025)
by: Bartoli, Pietro, et al.
Published: (2025)
On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Case
by: Dehrouyeh, Fatemeh, et al.
Published: (2024)
by: Dehrouyeh, Fatemeh, et al.
Published: (2024)
DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
by: Han, Lixiang, et al.
Published: (2024)
by: Han, Lixiang, et al.
Published: (2024)
TinyML Security: Exploring Vulnerabilities in Resource-Constrained Machine Learning Systems
by: Huckelberry, Jacob, et al.
Published: (2024)
by: Huckelberry, Jacob, et al.
Published: (2024)
On-device Online Learning and Semantic Management of TinyML Systems
by: Ren, Haoyu, et al.
Published: (2024)
by: Ren, Haoyu, et al.
Published: (2024)
U-TOE: Universal TinyML On-board Evaluation Toolkit for Low-Power IoT
by: Huang, Zhaolan, et al.
Published: (2023)
by: Huang, Zhaolan, et al.
Published: (2023)
Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data
by: Albaiz, Abdulrahman, et al.
Published: (2026)
by: Albaiz, Abdulrahman, et al.
Published: (2026)
TinyTNAS: GPU-Free, Time-Bound, Hardware-Aware Neural Architecture Search for TinyML Time Series Classification
by: Saha, Bidyut, et al.
Published: (2024)
by: Saha, Bidyut, et al.
Published: (2024)
Optimizing TinyML: The Impact of Reduced Data Acquisition Rates for Time Series Classification on Microcontrollers
by: Samanta, Riya, et al.
Published: (2024)
by: Samanta, Riya, et al.
Published: (2024)
Integration of TinyML and LargeML: A Survey of 6G and Beyond
by: Vu, Thai-Hoc, et al.
Published: (2025)
by: Vu, Thai-Hoc, et al.
Published: (2025)
Consolidating TinyML Lifecycle with Large Language Models: Reality, Illusion, or Opportunity?
by: Wu, Guanghan, et al.
Published: (2025)
by: Wu, Guanghan, et al.
Published: (2025)
msf-CNN: Patch-based Multi-Stage Fusion with Convolutional Neural Networks for TinyML
by: Huang, Zhaolan, et al.
Published: (2025)
by: Huang, Zhaolan, et al.
Published: (2025)
What changes after deployment? A survey on On-device Learning in TinyML
by: Pavan, Massimo, et al.
Published: (2026)
by: Pavan, Massimo, et al.
Published: (2026)
A Survey of TinyML Applications in Beekeeping for Hive Monitoring and Management
by: Sucipto, Willy, et al.
Published: (2025)
by: Sucipto, Willy, et al.
Published: (2025)
BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables
by: Samakovlis, Dimitrios, et al.
Published: (2024)
by: Samakovlis, Dimitrios, et al.
Published: (2024)
Optimising TinyML with Quantization and Distillation of Transformer and Mamba Models for Indoor Localisation on Edge Devices
by: Suwannaphong, Thanaphon, et al.
Published: (2024)
by: Suwannaphong, Thanaphon, et al.
Published: (2024)
SNAP-UQ: Self-supervised Next-Activation Prediction for Single-Pass Uncertainty in TinyML
by: Lamaakal, Ismail, et al.
Published: (2025)
by: Lamaakal, Ismail, et al.
Published: (2025)
Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning
by: Bao, Ziyuan, et al.
Published: (2025)
by: Bao, Ziyuan, et al.
Published: (2025)
Toward Attention-based TinyML: A Heterogeneous Accelerated Architecture and Automated Deployment Flow
by: Wiese, Philip, et al.
Published: (2024)
by: Wiese, Philip, et al.
Published: (2024)
QUTE: Quantifying Uncertainty in TinyML with Early-exit-assisted ensembles for model-monitoring
by: Ghanathe, Nikhil P, et al.
Published: (2024)
by: Ghanathe, Nikhil P, et al.
Published: (2024)
Hybrid Convolution and Vision Transformer NAS Search Space for TinyML Image Classification
by: Djajapermana, Mikhael, et al.
Published: (2025)
by: Djajapermana, Mikhael, et al.
Published: (2025)
OASI: Objective-Aware Surrogate Initialization for Multi-Objective Bayesian Optimization in TinyML Keyword Spotting
by: Garai, Soumen, et al.
Published: (2025)
by: Garai, Soumen, et al.
Published: (2025)
Simulating Battery-Powered TinyML Systems Optimised using Reinforcement Learning in Image-Based Anomaly Detection
by: Ping, Jared M., et al.
Published: (2024)
by: Ping, Jared M., et al.
Published: (2024)
Fed-Meta-Align: A Similarity-Aware Aggregation and Personalization Pipeline for Federated TinyML on Heterogeneous Data
by: Macharla, Hemanth, et al.
Published: (2025)
by: Macharla, Hemanth, et al.
Published: (2025)
DEBUG-HD: Debugging TinyML models on-device using Hyper-Dimensional computing
by: Ghanathe, Nikhil P, et al.
Published: (2024)
by: Ghanathe, Nikhil P, et al.
Published: (2024)
TCUQ: Single-Pass Uncertainty Quantification from Temporal Consistency with Streaming Conformal Calibration for TinyML
by: Lamaakal, Ismail, et al.
Published: (2025)
by: Lamaakal, Ismail, et al.
Published: (2025)
Towards Sustainable Personalized On-Device Human Activity Recognition with TinyML and Cloud-Enabled Auto Deployment
by: Saha, Bidyut, et al.
Published: (2024)
by: Saha, Bidyut, et al.
Published: (2024)
FERMI-ML: A Flexible and Resource-Efficient Memory-In-Situ SRAM Macro for TinyML acceleration
by: Lokhande, Mukul, et al.
Published: (2025)
by: Lokhande, Mukul, et al.
Published: (2025)
Similar Items
-
MLonMCU: TinyML Benchmarking with Fast Retargeting
by: van Kempen, Philipp, et al.
Published: (2023) -
TinySV: Speaker Verification in TinyML with On-device Learning
by: Pavan, Massimo, et al.
Published: (2024) -
TinyML-Enabled IoT for Sustainable Precision Irrigation
by: Taueatsoala, Kamogelo, et al.
Published: (2026) -
TinyML for Acoustic Anomaly Detection in IoT Sensor Networks
by: Almaini, Amar, et al.
Published: (2026) -
Accelerating TinyML Inference on Microcontrollers through Approximate Kernels
by: Armeniakos, Giorgos, et al.
Published: (2024)