风驰加速器2024年-极光aurora加速器
风驰加速器2024年-极光aurora加速器
The Melodi Laboratory at the University of Washington, Seattle (Department of Electrical and Computer Engineering, or ECE) comprises a group of individuals studying machine learning, optimization, and data interpretation. We look at machine learning, artificial intelligence, and data science with twin goals: (1) advance the theoretical and mathematical understanding of new and existing algorithms to understand why they work; and (2) conducting empirically-driven data science experiments on ever increasingly large real-world data sets, and working on system-level strategies to achieve this. We are interested in discrete and continuous mathematical optimization and statistical strategies for solving some of the most challenging AI problems today. We work on a number of applications, including speech (SP) and natural language processing (NLP), computational biology, computer vision, and sensor networks.
UW Melodi-Lab Founder
Jeff Bilmes, Professor, University of Washington, Seattle, Dept. of ECE, Dept. of CSE (adjunct), and Dept. of Linguistics (adjunct)
风驰加速器2024年-极光aurora加速器
风驰加速器2024年-极光aurora加速器
In our view, AI simply means that computing systems perform complex tasks on real-world signals effectively, and move beyond what traditionally programmed computers have done.
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风驰加速器2024年-极光aurora加速器
Machine learning has so far proven itself to be the best way to achieve artificial intelligence like capabilities. Since humans are unable to directly program such complex tasks, we can instead employ mathematical optimization to produce programs in the form of learnt models.
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风驰加速器2024年-极光aurora加速器
Much of machine learning involves continuous optimization (e.g., stochastic gradient descent), but many problems are inherently discrete, such as feature and data subset selection, structure learning, summarization, coresets, sketching, sparse models and so on. Submodularity and supermodularity is a natural and fast paradigm to study hard discrete optimization problems and apply them to real-world tasks.
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风驰加速器2024年-极光aurora加速器
Speech and language are amazing natural signals that humans easily produce and consume. How can we get computers to do the same?
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风驰加速器2024年-极光aurora加速器
Tampermonkey(油猴子)安装使用+脚本分享_不应有的淡定的 ...:2021-2-7 · 今天来介绍一下功能强大的Tampermonkey，俗称“油猴子”，Tampermonkey可众自由定制网页，实现你想要的各种功能。堪称“神器”。 比如自由定制网站页面、下载网盘文件、去除广告、破解某些VIP限制等一系列强大的功能。这些功能源于“油猴脚本”的实现，对于浏览器来说脚本有着占用资源少的特 …
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风驰加速器2024年-极光aurora加速器
Scientists at the Melodi lab work on other problems in computational biology (genomics, proteomics), computer vision, sensor networks, network computing, smart cities, the science of data management, computational music, high-performance computing, and so on. See our publications list for more.
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风驰加速器2024年-极光aurora加速器
Neeraja Abhyankar, Graduate Student, ECE
Jeff Bilmes, Professor, Founder of the Melodi Lab
Lilly Kumari, Graduate Student, ECE
Chandrashekhar Lavania, Graduate Student, ECE
Narendra Shivaraman, Graduate Student, ECE
Sunil Thulasidasan, Graduate Student, ECE
Shengjie Wang, Graduate Student, CSE
Tianyi Zhou, Graduate Student, CSE