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13 papers · 1 filter
DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections
Haebin Shin, Lei Ji, Xiao Liu +4
As numerous instruction-tuning datasets continue to emerge, dynamically balancing and optimizing their mixtures has become a critical challenge. To address this, we propose Dynamix…
Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons
Aref Ghoreishee, Abhishek Mishra, John Walsh +2
We propose a new ternary spiking neuron model to improve the representation capacity of binary spiking neurons in deep Q-learning. Although a ternary neuron model has recently been…
Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning
Khayrul Islam, Ryan F. Forelli, Jianzhong Han +6
Precise cell classification is essential in biomedical diagnostics and therapeutic monitoring, particularly for identifying diverse cell types involved in various diseases. Traditi…
Reliable edge machine learning hardware for scientific applications
Tommaso Baldi, Javier Campos, Ben Hawks +15
Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementatio…
Advancing Community Engaged Approaches to Identifying Structural Drivers of Racial Bias in Health Diagnostic Algorithms
Jill A. Kuhlberg, Irene Headen, Ellis A. Ballard +1
Much attention and concern has been raised recently about bias and the use of machine learning algorithms in healthcare, especially as it relates to perpetuating racial discriminat…
Early Diagnostic Prediction of Covid-19 using Gradient-Boosting Machine Model
Satvik Tripathi
With the huge spike in the COVID-19 cases across the globe and reverse transcriptase-polymerase chain reaction (RT-PCR) test remains a key component for rapid and accurate detectio…