Search Results for author:
Found 8 papers, 3 papers with code
Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion
Retrieval-based augmentations that aim to incorporate knowledge from an external database into language models have achieved great success in various knowledge-intensive (KI) tasks, such as question-answering and text generation.
Natural Language Understanding
Neural Architecture Search
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BiTrackGAN: Cascaded CycleGANs to Constraint Face Aging
With the increased accuracy of modern computer vision technology, many access control systems are equipped with face recognition functions for faster identification.
NFL: Robust Learned Index via Distribution Transformation
Based on the characteristics of the transformed keys, we propose a robust After-Flow Learned Index (AFLI).
A Fast Transformer-based General-Purpose Lossless Compressor
To ease this problem, this paper targets on cutting down the execution time of deep-learning-based compressors.
SEOFP-NET: Compression and Acceleration of Deep Neural Networks for Speech Enhancement Using Sign-Exponent-Only Floating-Points
In this paper, a novel sign-exponent-only floating-point network (SEOFP-NET) technique is proposed to compress the model size and accelerate the inference time for speech enhancement, a regression task of speech signal processing.
Speech Recovery for Real-World Self-powered Intermittent Devices
The incompleteness of speech inputs severely degrades the performance of all the related speech signal processing applications.
Variational Nested Dropout
Nested dropout is a variant of dropout operation that is able to order network parameters or features based on the pre-defined importance during training.
A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)
We evaluated the proposed EOFP quantization technique on two types of neural networks, namely, bidirectional long short-term memory (BLSTM) and fully convolutional neural network (FCN), on a speech enhancement task.
