9 citations · 24 across the 10 of their papers we have counts for
10 papers
Super Efficient Neural Network for Compression Artifacts Reduction and Super Resolution
Wen Ma, Qiuwen Lou, Arman Kazemi +2
Video quality can suffer from limited internet speed while being streamed by users. Compression artifacts start to appear when the bitrate decreases to match the available bandwidt…
COSIME: FeFET based Associative Memory for In-Memory Cosine Similarity Search
Che-Kai Liu, Haobang Chen, Mohsen Imani +8
In a number of machine learning models, an input query is searched across the trained class vectors to find the closest feature class vector in cosine similarity metric. However, p…
Associative Memory Based Experience Replay for Deep Reinforcement Learning
Mengyuan Li, Arman Kazemi, Ann Franchesca Laguna +1
Experience replay is an essential component in deep reinforcement learning (DRL), which stores the experiences and generates experiences for the agent to learn in real time. Recent…
Experimentally realized memristive memory augmented neural network
Ruibin Mao, Bo Wen, Yahui Zhao +8
Lifelong on-device learning is a key challenge for machine intelligence, and this requires learning from few, often single, samples. Memory augmented neural network has been propos…
MIMHD: Accurate and Efficient Hyperdimensional Inference Using Multi-Bit In-Memory Computing
Arman Kazemi, Mohammad Mehdi Sharifi, Zhuowen Zou +3
Hyperdimensional Computing (HDC) is an emerging computational framework that mimics important brain functions by operating over high-dimensional vectors, called hypervectors (HVs).…
Application-driven Design Exploration for Dense Ferroelectric Embedded Non-volatile Memories
Mohammad Mehdi Sharifi, Lillian Pentecost, Ramin Rajaei +8
The memory wall bottleneck is a key challenge across many data-intensive applications. Multi-level FeFET-based embedded non-volatile memories are a promising solution for denser an…