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leapfrog.nl | ||
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cccblog.org
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| | | | | TheComputing Community Consortium(CCC) sponsored another track in itsBlue Sky Ideas Conference Trackseriesat the 29th Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence (AAAI-15), January 25-30, 2015 in Austin, Texas. The purpose of this conference was to promote research in artificial intelligence (AI) and scientific exchange among AI researchers, practitioners, scientists, and engineers in affiliated disciplines. The goal of this track was topresent ideas and visions that canstimulate the research community to pursue newdirections, such as new problems, new applicationdomains, or new methodologies. The winning papers were: Machine Teaching: an Inverse Problem to Machine Learning and an Approach Toward Optimal Education Xiaojin Zhu (Department of Computer Sciences, [...] | |
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irisvanrooijcogsci.com
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| | | | | I've been asked, in various roles1, to give my opinion on the challenges posed by Large Language Models (LLMs)2, also known as "stochastic parrots" (Bender, Gebru, McMillan-Major, & Shmitchell, 2021), for assessing academic writing assignments. A concern seems to be that students legitimately can use these systems and that then we would be unable to... | |
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cccblog.org
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| | | | | The Computing Community Consortium (CCC) is sponsoring another track in itsBlue Sky Ideas Conference Trackseriesat the AAAI Conference on Artificial Intelligence on January 25-29, 2015 in Austin, Texas.The "Senior Member Presentation Track" provides an opportunity for established researchers in the AI community to give a broad talk on a well-developed body of research, an important new research area, or a promising new topic. These presentations should provide a "big picture" view, in contrast to regular papers, which may focus on a specific contribution. There are two subtracks for submissions of talk proposals for the Senior Member Presentation Track: Summary talks:broad talks on a well-developed body of research or an important [...] | |
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deepmind.google
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| | | According to empirical evidence from prior works, utility degradation in DP-SGD becomes more severe on larger neural network models - including the ones regularly used to achieve the best... | ||
