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Found 6 papers, 2 papers with code
MRI-based Multi-task Decoupling Learning for Alzheimer's Disease Detection and MMSE Score Prediction: A Multi-site Validation
First, a multi-task learning network is proposed to implement AD detection and MMSE score prediction, which exploits feature correlation by adding three multi-task interaction layers between the backbones of the two tasks.
Incentive Compatible Pareto Alignment for Multi-Source Large Graphs
Challenges of the problem include 1) how to align large-scale entities between sources to share information and 2) how to mitigate negative transfer from joint learning multi-source data.
Frame Stacking and Retaining for Recurrent Neural Network Acoustic Model
The system which combined frame retaining with frame stacking could reduces the time consumption of both training and decoding.
Deep LSTM for Large Vocabulary Continuous Speech Recognition
It is a competitive framework that LSTM models of more than 7 layers are successfully trained on Shenma voice search data in Mandarin and they outperform the deep LSTM models trained by conventional approach.
Exponential Moving Average Model in Parallel Speech Recognition Training
As training data rapid growth, large-scale parallel training with multi-GPUs cluster is widely applied in the neural network model learning currently. We present a new approach that applies exponential moving average method in large-scale parallel training of neural network model.
Speculate-Correct Error Bounds for k-Nearest Neighbor Classifiers
We introduce the speculate-correct method to derive error bounds for local classifiers.
