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Found 23 papers, 3 papers with code
Spatial-Aware Image Retrieval: A Hyperdimensional Computing Approach for Efficient Similarity Hashing
Our work introduces a transformative image hashing framework enabling spatial-aware conditional retrieval.
EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration
Detecting marine objects inshore presents challenges owing to algorithmic intricacies and complexities in system deployment.
Self-Attention Based Semantic Decomposition in Vector Symbolic Architectures
In this work, we introduce a new variant of the resonator network, based on self-attention based update rules in the iterative search problem.
TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection
Nevertheless, the naive application of VLMs leads to sub-optimal quality, due to the misalignment between embeddings of object images and their visual attributes, which are mainly adjective phrases.
HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning
When conducting cross-models and cross-platforms comparison, HDReason yields an average 4. 2x higher performance and 3. 4x better energy efficiency with similar accuracy versus the state-of-the-art FPGA-based GCN training platform.
HEAL: Brain-inspired Hyperdimensional Efficient Active Learning
Drawing inspiration from the outstanding learning capability of our human brains, Hyperdimensional Computing (HDC) emerges as a novel computing paradigm, and it leverages high-dimensional vector presentation and operations for brain-like lightweight Machine Learning (ML).
A Plug-in Tiny AI Module for Intelligent and Selective Sensor Data Transmission
To enhance the framework's performance, the training process is customized and a "lazy" sensor deactivation strategy utilizing temporal information is introduced.
HyperSense: Accelerating Hyper-Dimensional Computing for Intelligent Sensor Data Processing
Introducing HyperSense, our co-designed hardware and software system efficiently controls Analog-to-Digital Converter (ADC) modules' data generation rate based on object presence predictions in sensor data.
Towards Efficient Hyperdimensional Computing Using Photonics
Over the past few years, silicon photonics-based computing has emerged as a promising alternative to CMOS-based computing for Deep Neural Networks (DNN).
Learning from Hypervectors: A Survey on Hypervector Encoding
It zeroes in on the HDC system input and the generation of hypervectors, directly influencing the hypervector encoding process.
Ethosight: A Reasoning-Guided Iterative Learning System for Nuanced Perception based on Joint-Embedding & Contextual Label Affinity
Traditional computer vision models often necessitate extensive data acquisition, annotation, and validation.
Late Breaking Results: Scalable and Efficient Hyperdimensional Computing for Network Intrusion Detection
Cybersecurity has emerged as a critical challenge for the industry.
DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification
Brain-inspired hyperdimensional computing (HDC) has been recently considered a promising learning approach for resource-constrained devices.
Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing
Considering the significant role of wearable devices in monitoring human body parameters, on-device learning can be utilized to build personalized models for behavioral and physiological patterns, and provide data privacy for users at the same time.
Modeling and Predicting Transistor Aging under Workload Dependency using Machine Learning
The pivotal issue of reliability is one of colossal concern for circuit designers.
Efficient Off-Policy Reinforcement Learning via Brain-Inspired Computing
Our evaluation shows QHD capability for real-time learning, providing 34. 6 times speedup and significantly better quality of learning than DQN.
Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
Particularly, Spiking Neural Networks (SNNs) and HyperDimensional Computing (HDC) have shown promising results in enabling efficient and robust cognitive learning.
Trustworthy AI Inference Systems: An Industry Research View
Additionally, such systems should also use Privacy-Enhancing Technologies (PETs) to protect customers' data at any time.
Prive-HD: Privacy-Preserved Hyperdimensional Computing
In this paper, we target privacy-preserving training and inference of brain-inspired Hyperdimensional (HD) computing, a new learning algorithm that is gaining traction due to its light-weight computation and robustness particularly appealing for edge devices with tight constraints.
QubitHD: A Stochastic Acceleration Method for HD Computing-Based Machine Learning
It is a promising solution for achieving high energy efficiency in different machine learning tasks, such as classification, semi-supervised learning, and clustering.
Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces
Since the attacker gets to design his classifier based on the defense design, we first demonstrate that at least one technique for generating adversarial-example based traces fails to protect against an attacker using adversarial training for robust classification.
Website Fingerprinting Defense
Cryptography and Security
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework
To enable in-memory processing, RAPIDNN reinterprets a DNN model and maps it into a specialized accelerator, which is designed using non-volatile memory blocks that model four fundamental DNN operations, i. e., multiplication, addition, activation functions, and pooling.
Modified Relay Selection and Circuit Selection for Faster Tor
In this paper, we examine both the process of selecting among pre-built circuits and the process of selecting the path of relays for use in building new circuits to improve performance while maintaining anonymity.
Cryptography and Security
