Search Results for author:
Found 9 papers, 2 papers with code
Optimizing TinyML: The Impact of Reduced Data Acquisition Rates for Time Series Classification on Microcontrollers
For example, a 75\% reduction in acquisition rate for MITBIH and PTB datasets led to a 60\% decrease in RAM usage, 75\% reduction in MAC operations, 74\% decrease in latency, and 70\% reduction in energy consumption, without accuracy loss.
CTG-KrEW: Generating Synthetic Structured Contextually Correlated Content by Conditional Tabular GAN with K-Means Clustering and Efficient Word Embedding
To address these problems, we introduce a novel framework, CTGKrEW (Conditional Tabular GAN with KMeans Clustering and Word Embedding), which is adept at generating realistic synthetic tabular data where attributes are collections of semantically and contextually coherent words.
TinyTNAS: GPU-Free, Time-Bound, Hardware-Aware Neural Architecture Search for TinyML Time Series Classification
In this work, we present TinyTNAS, a novel hardware-aware multi-objective Neural Architecture Search (NAS) tool specifically designed for TinyML time series classification.
Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots
ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data.
What You Like: Generating Explainable Topical Recommendations for Twitter Using Social Annotations
With over 500 million tweets posted per day, in Twitter, it is difficult for Twitter users to discover interesting content from the deluge of uninteresting posts.
Machine Assistance for Credit Card Approval? Random Wheel can Recommend and Explain
In this work, we have used an enhanced version of random wheel to facilitate a trustworthy recommendation for credit card approval process.
Tensor-Train Long Short-Term Memory for Monaural Speech Enhancement
Based on this TT-LSTM units, we proposed a deep TensorNet model for single-channel speech enhancement task.
SPIN: A Fast and Scalable Matrix Inversion Method in Apache Spark
The growth of big data in domains such as Earth Sciences, Social Networks, Physical Sciences, etc.
Distributed, Parallel, and Cluster Computing
Learning Representations from Road Network for End-to-End Urban Growth Simulation
From our experiences in the past, we have seen that the growth of cities is very much dependent on the transportation networks.
