On-device research index

arXiv research

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.

168,695 papers · 148 categories

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3 results for “OS-ELM”

The Integrity of Machine Learning Algorithms against Software Defect Predictioncs.SE

OS-ELM outperforms other classifiers in software defect prediction.

problem Predicting software defects from imbalanced datasets.

method OS-ELM, oversampling with noise filtering, comparison with other classifiers.

result OS-ELM outperforms other classifiers in recall and balanced accuracy.

Machine Learning Software Defect Prediction Imbalanced Data OS-ELM Oversampling

2020-09-05abs ↗pdf ↗

An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learningcs.LG

A lightweight FPGA-based reinforcement learning approach for edge devices.

problem Resource constraints and inefficiency of DQN on edge devices.

method OS-ELM based training algorithm and L2 regularization for stability.

result 29.77x and 89.40x faster than conventional DQN-based approach for CartPole-v0 task.

FPGA Reinforcement Learning Edge Devices OS-ELM L2 Regularization

2020-05-10abs ↗pdf ↗

An On-Device Federated Learning Approach for Cooperative Model Update between Edge Devicescs.LG

On-device federated learning updates edge models by exchanging trained results.

problem Limited training data at edge devices due to model drift.

method OS-ELM for sequential training and autoencoder for anomaly detection, combined with federated learning.

result The proposed approach produces a merged model as accurately as traditional methods with lower costs.

federated learning on-device learning edge devices model update neural networks

2020-02-27abs ↗pdf ↗