scholarly journals A conversation with Tengyu Ma

Ubiquity ◽  
2021 ◽  
Vol 2021 (September) ◽  
pp. 1-5
Author(s):  
Bushra Anjum

In this interview, Ubiquity's senior editor Dr. Bushra Anjum chats with Dr. Tengyu Ma, an assistant professor of Computer Science and Statistics at Stanford University. They discuss Dr. Ma's research that aims to bridge the gap between theory and practice in deep learning by developing novel mathematical tools to understand complex and mysterious deep learning systems.

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2514
Author(s):  
Tharindu Kaluarachchi ◽  
Andrew Reis ◽  
Suranga Nanayakkara

After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or Machine Learning (ML) field is undergoing rapid growth concerning research and real-world application development. Deep Learning has generated complexities in algorithms, and researchers and users have raised concerns regarding the usability and adoptability of Deep Learning systems. These concerns, coupled with the increasing human-AI interactions, have created the emerging field that is Human-Centered Machine Learning (HCML). We present this review paper as an overview and analysis of existing work in HCML related to DL. Firstly, we collaborated with field domain experts to develop a working definition for HCML. Secondly, through a systematic literature review, we analyze and classify 162 publications that fall within HCML. Our classification is based on aspects including contribution type, application area, and focused human categories. Finally, we analyze the topology of the HCML landscape by identifying research gaps, highlighting conflicting interpretations, addressing current challenges, and presenting future HCML research opportunities.


2021 ◽  
Author(s):  
Mizuho Mori ◽  
Yoshiko Ariji ◽  
Motoki Fukuda ◽  
Tomoya Kitano ◽  
Takuma Funakoshi ◽  
...  

Abstract Objectives The aim of the present study was to create and test an automatic system for assessing the technical quality of positioning in periapical radiography of the maxillary canines using deep learning classification and segmentation techniques. Methods We created and tested two deep learning systems using 500 periapical radiographs (250 each of good- and bad-quality images). We assigned 350, 70, and 80 images as the training, validation, and test datasets, respectively. The learning model of system 1 was created with only the classification process, whereas system 2 consisted of both the segmentation and classification models. In each model, 500 epochs of training were performed using AlexNet and U-net for classification and segmentation, respectively. The segmentation results were evaluated by the intersection over union method, with values of 0.6 or more considered as success. The classification results were compared between the two systems. Results The segmentation performance of system 2 was recall, precision, and F measure of 0.937, 0.961, and 0.949, respectively. System 2 showed better classification performance values than those obtained by system 1. The area under the receiver operating characteristic curve values differed significantly between system 1 (0.649) and system 2 (0.927). Conclusions The deep learning systems we created appeared to have potential benefits in evaluation of the technical positioning quality of periapical radiographs through the use of segmentation and classification functions.


2021 ◽  
pp. 117-129
Author(s):  
Thomas E. Schindler

This chapter picks up the story of Esther’s life after she and her husband moved to Stanford University in Palo Alto, California, in 1959, and Joshua became chairman of the newly formed Genetics Department. The Lederbergs separated in September 1966, divorced in 1967, and a year later, Joshua married Marguerite Stein, a thirty-year-old divorcee and pediatrician. Esther Lederberg collaborated with her husband less and less after the move to Stanford. When they separated, Esther was suddenly exiled from the laboratory, cut off from research funding, and facing uncertain employment prospects. After winning the Nobel Prize, Joshua began collaborating with new colleagues in chemistry, engineering, and computer science. He became an international proponent of exobiology. In 1976, Esther Lederberg became director of the Plasmid Reference Center of Stanford University. Although it was not a research position, she applied her extensive knowledge of plasmids and bacteria to curating one of the largest collections in the world. She held this position until her retirement in 1985.


2021 ◽  
pp. 161-176
Author(s):  
Xinle Liu ◽  
Akinori Mitani ◽  
Terry Spitz ◽  
Derek J. Wu ◽  
Joseph R. Ledsam

Author(s):  
Swagath Venkataramani ◽  
Vijayalakshmi Srinivasan ◽  
Jungwook Choi ◽  
Philip Heidelberger ◽  
Leland Chang ◽  
...  

2020 ◽  
Vol 216 ◽  
pp. 140-146
Author(s):  
Hee Kyung Yang ◽  
Young Jae Kim ◽  
Jae Yun Sung ◽  
Dong Hyun Kim ◽  
Kwang Gi Kim ◽  
...  

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