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05/12/2023
Mem-Rec: Memory Efficient Recommendation System using Alternative Representation
Deep learning-based recommendation systems (e.g., DLRMs) are widely used...
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01/23/2023
DODEM: DOuble DEfense Mechanism Against Adversarial Attacks Towards Secure Industrial Internet of Things Analytics
Industrial Internet of Things (I-IoT) is a collaboration of devices, sen...
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01/17/2023
Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks
Federated Learning (FL) has gained increasing interest in recent years a...
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11/15/2022
Massively Parallel Open Modification Spectral Library Searching with Hyperdimensional Computing
Mass spectrometry, commonly used for protein identification, generates a...
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11/10/2022
RAPIDx: High-performance ReRAM Processing in-Memory Accelerator for Sequence Alignment
Genome sequence alignment is the core of many biological applications. T...
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09/20/2022
Streaming Encoding Algorithms for Scalable Hyperdimensional Computing
Hyperdimensional computing (HDC) is a paradigm for data representation a...
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08/24/2022
SCALE: Online Self-Supervised Lifelong Learning without Prior Knowledge
Unsupervised lifelong learning refers to the ability to learn over time ...
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04/26/2022
MemFHE: End-to-End Computing with Fully Homomorphic Encryption in Memory
The increasing amount of data and the growing complexity of problems has...
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03/14/2022
RES-HD: Resilient Intelligent Fault Diagnosis Against Adversarial Attacks Using Hyper-Dimensional Computing
Industrial Internet of Things (I-IoT) enables fully automated production...
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10/14/2020
Theoretical Foundations of Hyperdimensional Computing
Hyperdimensional (HD) computing is a set of neurally inspired methods fo...
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07/20/2020
SHEARer: Highly-Efficient Hyperdimensional Computing by Software-Hardware Enabled Multifold Approximation
Hyperdimensional computing (HD) is an emerging paradigm for machine lear...
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05/14/2020
Prive-HD: Privacy-Preserved Hyperdimensional Computing
The privacy of data is a major challenge in machine learning as a traine...
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02/05/2020
FPGA Acceleration of Sequence Alignment: A Survey
Genomics is changing our understanding of humans, evolution, diseases, a...
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12/16/2019
A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning
Recent progress on few-shot learning has largely re-lied on annotated da...
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11/21/2019
AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning
There is an increasing number of pre-trained deep neural network models....
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11/17/2019
FPGA Energy Efficiency by Leveraging Thermal Margin
Cutting edge FPGAs are not energy efficient as conventionally presumed t...
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09/25/2019
Learning with Long-term Remembering: Following the Lead of Mixed Stochastic Gradient
Current deep neural networks can achieve remarkable performance on a sin...
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08/18/2019
Workload-Aware Opportunistic Energy Efficiency in Multi-FPGA Platforms
The continuous growth of big data applications with high computational a...
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02/03/2019
Depthwise Convolution is All You Need for Learning Multiple Visual Domains
There is a growing interest in designing models that can deal with image...
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11/21/2018
SpotTune: Transfer Learning through Adaptive Fine-tuning
Transfer learning, which allows a source task to affect the inductive bi...
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06/15/2018