8 citations · 32 across the 10 of their papers we have counts for
10 papers
Spectrally Adaptive Common Spatial Patterns
Mahta Mousavi, Eric Lybrand, Shuangquan Feng +3
The method of Common Spatial Patterns (CSP) is widely used for feature extraction of electroencephalography (EEG) data, such as in motor imagery brain-computer interface (BCI) syst…
Learning compact generalizable neural representations supporting perceptual grouping
Vijay Veerabadran, Virginia R. de Sa
Work at the intersection of vision science and deep learning is starting to explore the efficacy of deep convolutional networks (DCNs) and recurrent networks in solving perceptual…
Deep Transfer Learning with Ridge Regression
Shuai Tang, Virginia R. de Sa
The large amount of online data and vast array of computing resources enable current researchers in both industry and academia to employ the power of deep learning with neural netw…
An Empirical Study on Post-processing Methods for Word Embeddings
Shuai Tang, Mahta Mousavi, Virginia R. de Sa
Word embeddings learnt from large corpora have been adopted in various applications in natural language processing and served as the general input representations to learning syste…
A Simple Recurrent Unit with Reduced Tensor Product Representations
Shuai Tang, Paul Smolensky, Virginia R. de Sa
idely used recurrent units, including Long-short Term Memory (LSTM) and the Gated Recurrent Unit (GRU), perform well on natural language tasks, but their ability to learn structure…
Improving Sentence Representations with Consensus Maximisation
Shuai Tang, Virginia R. de Sa
Consensus maximisation learning can provide self-supervision when different views are available of the same data. The distributional hypothesis provides another form of useful self…