3 citations · 5 across the 5 of their papers we have counts for
5 papers
Estimation of embedding vectors in high dimensions
Golara Ahmadi Azar, Melika Emami, Alyson Fletcher +1
Embeddings are a basic initial feature extraction step in many machine learning models, particularly in natural language processing. An embedding attempts to map data tokens to a l…
A Deep Learning Sequential Decoder for Transient High-Density Electromyography in Hand Gesture Recognition Using Subject-Embedded Transfer Learning
Golara Ahmadi Azar, Qin Hu, Melika Emami +3
Hand gesture recognition (HGR) has gained significant attention due to the increasing use of AI-powered human-computer interfaces that can interpret the deep spatiotemporal dynamic…
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions
Mojtaba Sahraee-Ardakan, Melikasadat Emami, Parthe Pandit +2
Empirical observation of high dimensional phenomena, such as the double descent behaviour, has attracted a lot of interest in understanding classical techniques such as kernel meth…
Low-Rank Nonlinear Decoding of -ECoG from the Primary Auditory Cortex
Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit +6
This paper considers the problem of neural decoding from parallel neural measurements systems such as micro-electrocorticography (-ECoG). In systems with large numbers of array…
Input-Output Equivalence of Unitary and Contractive RNNs
M. Emami, M. Sahraee-Ardakan, S. Rangan +1
Unitary recurrent neural networks (URNNs) have been proposed as a method to overcome the vanishing and exploding gradient problem in modeling data with long-term dependencies. A ba…