# DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification

arXiv: https://arxiv.org/abs/2304.05503 · HTML: https://mlsanity.com/paper/2304.05503/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 30 references that are in the map.
- First posted on arXiv 11 Apr 2023.

## Builds on (most cited first, 4 of 4)

- [Federated Learning: Challenges, Methods, and Future Directions](https://mlsanity.com/paper/1908.07873/) (2019)
- [TensorFlow Lite Micro: Embedded Machine Learning on TinyML Systems](https://mlsanity.com/paper/2010.08678/) (2020)
- [Classification using Hyperdimensional Computing: A Review](https://mlsanity.com/paper/2004.11204/) (2020)
- [Edge-Host Partitioning of Deep Neural Networks with Feature Space Encoding for Resource-Constrained Internet-of-Things Platforms](https://mlsanity.com/paper/1802.03835/) (2018)

## Built on by (most cited first, 13 of 13)

- [Learning from Hypervectors: A Survey on Hypervector Encoding](https://mlsanity.com/paper/2308.00685/) (2023)
- [Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception](https://mlsanity.com/paper/2503.20011/) (2025)
- [DOMINO: Domain-invariant Hyperdimensional Classification for Multi-Sensor Time Series Data](https://mlsanity.com/paper/2308.03295/) (2023)
- [Robust and Scalable Hyperdimensional Computing With Brain-Like Neural Adaptations](https://mlsanity.com/paper/2311.07705/) (2023)
- [DecoHD: Decomposed Hyperdimensional Classification under Extreme Memory Budgets](https://mlsanity.com/paper/2511.03911/) (2025)
- [LogHD: Robust Compression of Hyperdimensional Classifiers via Logarithmic Class-Axis Reduction](https://mlsanity.com/paper/2511.03938/) (2025)
- [Enhanced Detection of Transdermal Alcohol Levels Using Hyperdimensional Computing on Embedded Devices](https://mlsanity.com/paper/2403.12323/) (2024)
- [DEBUG-HD: Debugging TinyML models on-device using Hyper-Dimensional computing](https://mlsanity.com/paper/2411.10692/) (2024)
- [Transformer-Based Contrastive Meta-Learning For Low-Resource Generalizable Activity Recognition](https://mlsanity.com/paper/2412.20290/) (2024)
- [ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing](https://mlsanity.com/paper/2604.21280/) (2026)
- [BiHDTrans: binary hyperdimensional transformer for efficient multivariate time series classification](https://mlsanity.com/paper/2509.24425/) (2025)
- [QeHDC: Hyperdimensional Computing based on Quantum-enhanced binding and SuperClass Construction](https://mlsanity.com/paper/2606.22421/) (2026)
- [CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving](https://mlsanity.com/paper/2608.09202/) (2026)

## Abstract (arXiv)

Brain-inspired hyperdimensional computing (HDC) has been recently considered a promising learning approach for resource-constrained devices. However, existing approaches use static encoders that are never updated during the learning process. Consequently, it requires a very high dimensionality to achieve adequate accuracy, severely lowering the encoding and training efficiency. In this paper, we propose DistHD, a novel dynamic encoding technique for HDC adaptive learning that effectively identifies and regenerates dimensions that mislead the classification and compromise the learning quality. Our proposed algorithm DistHD successfully accelerates the learning process and achieves the desired accuracy with considerably lower dimensionality.