A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Optimized neural networks for Edge TPU achieve high accuracy in real-time image classification.
This paper presents a fast Bayesian filtering technique for state estimation.
Implantable, closed-loop devices for automated early detection and stimulation of epileptic seizures are promising treatment options for patients with severe epilepsy that cannot be treated with traditional means. Most approaches for early seizure detection in the literature are, however, not optimized for implementati…
We implement a differentiable Neural Architecture Search (NAS) method inspired by FBNet for discovering neural networks that are heavily optimized for a particular target device. The FBNet NAS method discovers a neural network from a given search space by optimizing over a loss function which accounts for accuracy and …
Simpler models outperform deep architectures with proper preprocessing and tuning.
Network quantization is one of the most hardware friendly techniques to enable the deployment of convolutional neural networks (CNNs) on low-power mobile devices. Recent network quantization techniques quantize each weight kernel in a convolutional layer independently for higher inference accuracy, since the weight ker…
Two approaches scale up DNN optimization for diverse edge devices.
HOLMES improves real-time model serving for ICU patients, balancing accuracy and speed.
A new method for efficiently updating large-scale matrices in real-time.