Search Results - deliang+fan

14 Results Sort By:
Full-stack Obfuscation Tool to Mitigate Neural Architecture Stealing
The architecture information of a Deep Neural Network (DNN) model is considered a valuable, sensitive piece of property for a company. Knowledge of a DNN’s exact architecture allows any adversary to build a substitute model and use this substitute model to launch devastating adversarial attacks. Side-channel based DNN architecture stealing can...
Published: 2/13/2025   |   Inventor(s): Jingtao Li, Chaitali Chakrabarti, Deliang Fan, Adnan Siraj Rakin
Keywords(s): Artificial Intelligence, Cyber Security, Defense Applications, Machine Learning, Neural Computing, PS-Computing and Information Technology
Category(s): Computing & Information Technology, Physical Science, Intelligence & Security
Single-Cycle Processing-in-SRAM Logic Circuit Design
Traditional von-Neumann computing architectures, such as CPUs and GPUs, demonstrate limitations in memory bandwidth and energy efficiency. However, their high demand lies in their programmability and flexible functionality. Such platforms execute a wide spectrum of bit-wise logic and arithmetic operations. In this regard, recent application-specific...
Published: 2/13/2025   |   Inventor(s): Deliang Fan, Shaahin Angizi
Keywords(s): Algorithm Development, Circuits, Computational Machine, Computing Architecture, Electronics, Memory, PS-Computing and Information Technology
Category(s): Computing & Information Technology, Physical Science
Learning Sparse Features for Self-Supervised Learning with Contrastive Dual Gating
The success of conventional supervised learning relies on large-scale labeled datasets to achieve high accuracy. However, annotating millions of data samples is labor-intensive and time-consuming. This promotes self-supervised learning as an attractive solution with artificial labels being used instead of human-annotated ones for training. Contrastive...
Published: 2/13/2025   |   Inventor(s): Jae-Sun Seo, Jian Meng, Li Yang, Deliang Fan
Keywords(s): Algorithm Development, Machine Learning, Performance Optimization, PS-Computing and Information Technology
Category(s): Computing & Information Technology, Physical Science
Temperature-Resilient RRAM-Based In-Memory Computing for DNN Inference
Deep neural networks (DNNs) have shown extraordinary performance in recent years for various applications, including image classification, object detection, speech recognition, etc. Accuracy-driven DNN architectures tend to increase model sizes and computations in a very fast pace, demanding a massive amount of hardware resources. Frequent communication...
Published: 2/13/2025   |   Inventor(s): Jae-Sun Seo, Jian Meng, Li Yang, Deliang Fan
Keywords(s): Algorithm Development, Machine Learning, Memory, Neural Computing, PS-Computing and Information Technology
Category(s): Computing & Information Technology, Physical Science
Masked-Based Learning Method for Neural Network Multiple Task Adaption
Nowadays, one practical limitation of deep neural networks (DNNs) is their high degree of specialization to a single task. This motivates researchers to develop algorithms that can adapt the DNN model to multiple tasks sequentially, while still performing well on past tasks. This process of gradually adapting the DNN model to learn from different...
Published: 2/13/2025   |   Inventor(s): Deliang Fan, Fan Zhang, Li Yang
Keywords(s): Algorithm Development, Computational Machine, Computing Architecture, Cyber-Physical System, Machine Learning, Neural Computing
Category(s): Computing & Information Technology, Physical Science
Memory Efficient, Multi-Domain On-Device Machine Learning
­One practical limitation of deep neural network (DNN) is its high degree of specialization to a single task or domain (e.g., one visual domain). This motivates the development of algorithms that can adapt DNN model to multiple domains sequentially while still performing well on past domains. This is known as multi-domain learning. Conventional...
Published: 2/13/2025   |   Inventor(s): Li Yang, Deliang Fan, Adnan Siraj Rakin
Keywords(s): Algorithm Development, Artificial Intelligence, Machine Learning, On-device learning, PS-Computing and Information Technology
Category(s): Physical Science, Computing & Information Technology
Processing-In-Memory (PIM) Platform for mRNA Quantification
­The study of human genetics is a rapidly expanding field, fueled in part by developments in large-scale protein and genomic sequencing technologies. Biopharmaceutical companies and modern healthcare rely heavily on sequencing technologies and the acquired data to develop new drugs and provide effective treatments to patients. However, the results...
Published: 2/13/2025   |   Inventor(s): Deliang Fan, Fan Zhang, Shaahin Angizi
Keywords(s): Algorithm Development, Biomarker discovery, Computing Architecture, DNA and protein sequencing, Genomics, Proteomics, Sequencing
Category(s): Physical Science, Computing & Information Technology, Bioanalytical Assays, Chemistries & Devices, Genomic Assays/Reagents/Tools
Fast and Efficient Max/Min Searching in DRAM
­In the era of big data, min/max searching from bulk data arrays is one of the most important and widely used fundamental operations in data-intensive applications such as sorting, ranking, bioinformatics, data mining, graph processing, and route planning. Online news and social media require real-time ranking using fast min/max searching from...
Published: 2/13/2025   |   Inventor(s): Deliang Fan, Fan Zhang, Shaahin Angizi
Keywords(s): Algorithm Development, Computational Machine, Computing Architecture, Data Center, Data Mining, Microprocessors, Processing
Category(s): Computing & Information Technology, Physical Science
Binary Neural Network for Improved Accuracy and Defense Against Bit-Flip Attacks
­Recently, Deep Neural Networks (DNNs) have been deployed in many safety-critical applications. The security of DNN models can be compromised by adversarial input examples, where the adversary maliciously crafts and adds input noise to fool a DNN model. The perturbation of model parameters (e.g., weight) is another security concern, one that relates...
Published: 2/13/2025   |   Inventor(s): Deliang Fan, Adnan Siraj Rakin, Li Yang, Chaitali Chakrabarti, Yu Cao, Jae-Sun Seo, Jingtao Li
Keywords(s): Algorithm Development, Artificial Intelligence, Cyber Security, Defense Applications, Machine Learning, Neural Computing
Category(s): Physical Science, Intelligence & Security, Wireless & Networking, Computing & Information Technology
Hardware-Noise-Aware Training for Improved Accuracy of In-Memory-Computing-Based Deep Neural Networks
­Background Deep neural networks (DNNs) have been very successful in large-scale recognition tasks, but they exhibit large computation and memory requirements. To address the memory bottleneck of digital DNN hardware accelerators, in-memory computing (IMC) designs have been presented to perform analog DNN computations inside the memory. Recent IMC...
Published: 2/13/2025   |   Inventor(s): Sai Kiran Cherupally, Jae-Sun Seo, Deliang Fan, Shihui Yin, Jian Meng
Keywords(s): Algorithm Development, Artificial Intelligence, Electronics, Neural Computing
Category(s): Physical Science, Computing & Information Technology, Intelligence & Security
1 2