TII’s Falcon H1R 7B can out-reason models up to 7x its size — and it’s (mostly) open

According to TII’s technical report, the hybrid approach allows Falcon H1R 7B to maintain high throughput even as response ...

AI approach takes optical system design from months to milliseconds

A team of researchers at Penn State have devised a new, streamlined approach to designing metasurfaces, a class of engineered ...
eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
IEEE

Hyperparameter Optimization Method for Affine Projection Algorithm Based on Deep Unrolling

Abstract: In this letter, we propose a hyperparameter optimization method for adaptive filtering based on deep unrolling, termed the deep unrolling affine projection (DAP) algorithm. The core idea is ...
Scientific Research Publishing

Soper, D.S. (2021) Greed Is Good: Rapid Hyperparameter Optimization and Model Selection Using Greedy K-Fold Cross Validation. Electronics, 10, Article No. 1973.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Frontiers

Federated learning framework for IoT intrusion detection using tab transformer and nature-inspired hyperparameter optimization

Intrusion detection has been of prime concern in the Internet of Things (IoT) environment due to the rapid increase in cyber threats. Majority of traditional intrusion detection systems (IDSs) rely on ...
IEEE

pFedDHPO: A Differentiable Approach for Personalized Hyperparameter Optimization in Federated Learning

Abstract: Hyperparameter optimization (HPO) is crucial for federated learning (FL) performance. Given the inherent data heterogeneity across clients, recent research has focused on providing ...
GitHub

Adaptive Hyperparameter Optimization for Author Name Disambiguation

In this paper, we propose a block-based hyperparameter optimization algorithm. Experiments on 6 state-of-the-art algorithms and 11 public datasets show that our method can significantly improve the ...