activity
20202023
most citedXTab: Cross-table Pretraining for Tabular Transformers

7 citations · 10 across the 6 of their papers we have counts for

collaborators

7 papers

eess.SP2023

Enhancing Epileptic Seizure Detection with EEG Feature Embeddings

Arman Zarei, Bingzhao Zhu, Mahsa Shoaran

Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capa…

cs.LG20237 cited

XTab: Cross-table Pretraining for Tabular Transformers

Bingzhao Zhu, Xingjian Shi, Nick Erickson +3

The success of self-supervised learning in computer vision and natural language processing has motivated pretraining methods on tabular data. However, most existing tabular self-su…

cs.LG20211 cited

Tree in Tree: from Decision Trees to Decision Graphs

Bingzhao Zhu, Mahsa Shoaran

Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree…

eess.SP2021

Closed-Loop Neural Prostheses with On-Chip Intelligence: A Review and A Low-Latency Machine Learning Model for Brain State Detection

Bingzhao Zhu, Uisub Shin, Mahsa Shoaran

The application of closed-loop approaches in systems neuroscience and therapeutic stimulation holds great promise for revolutionizing our understanding of the brain and for develop…

cs.LG2021

Unsupervised Domain Adaptation for Cross-Subject Few-Shot Neurological Symptom Detection

Bingzhao Zhu, Mahsa Shoaran

Modern machine learning tools have shown promise in detecting symptoms of neurological disorders. However, current approaches typically train a unique classifier for each subject.…

cs.AR2020

Closed-Loop Neural Interfaces with Embedded Machine Learning

Bingzhao Zhu, Uisub Shin, Mahsa Shoaran

Neural interfaces capable of multi-site electrical recording, on-site signal classification, and closed-loop therapy are critical for the diagnosis and treatment of neurological di…