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The MADLab is a University Center of Excellence supported by the Air Force Office of Sponsored Research (AFOSR) and the Air Force Research Lab (AFRL).  The Center is developing the next-generation of Machine Learning (ML) theory, algorithms, and applications.

ML has advanced considerably in recent years, but mostly in well-defined domains using huge amounts of human-labeled training data. Many application domains may not be so well-defined and, while data rich, they tend to be label poor. This issue has limited the impact of state-of-the-art ML theory and methods in specialized applications. Furthermore, the decision-making mechanisms of existing ML systems are often difficult to interpret, calling into question the use of such systems in mission-critical operations. Adding to these challenges are the need to fuse information from multiple sensors, adapt to dynamic environments, cope with missing or severely corrupted data, design more efficient ML hardware, and combat adversarial forces aiming to disrupt ML systems.

These issues present several grand challenges for ML that are the Center’s research foci:

    • new ML theory and methods to enable the rapid training and/or adaptation of predictors using a small number of labeled training examples;
    • 平心在线官网_“用爱发电”照样“用钱发电”?B站的“破圈 ...:平心在线:平心在线手机版_QuestMobile2021儿童经济洞察讲述平心在线:互联网的信息渠道多元、社交分享、内容种草、KOL带货等新玩法,正在加速推动“儿童经济细分领域”的闭环,详情请参见QuestMobile儿童经济洞察报告 作者 / 王梓健 泉源 /...
    • ML algorithms that are interpretable as well as robust to dynamic operational conditions, missing data, and sensor failures; and
    • new ML technology that is robust to adversarial attacks and data contamination.

The Center is also spearheading the development of new ML technology tailored to specialized applications, as well as training the next generation of machine learning researchers and practitioners.

佛跳墙vp官方版2023

佛跳墙vp官方版2023

SysML Conference in Stanford, California February 15-16, 2018 was a new conference targeting research at the intersection of systems and machine learning.

佛跳墙vp官方版2023

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佛跳墙vp官方版2023

就爱加速器 就爱加速官网 AF Research Laboratory
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University of Chicago

 

佛跳墙vp官方版2023

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佛跳墙vp官方版2023

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MADLab UCoE
Grainger Institute for Engineering
Engineering Centers Building
1550 Engineering Dr., Madison, WI 53706

gie@engr.wisc.edu
608-265-7953