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Institution

University of California

EducationOakland, California, United States
About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.


Papers
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TL;DR: WaveGAN as mentioned in this paper uses GANs to synthesize one second slices of audio waveforms with global coherence, suitable for sound effect generation, which can also synthesize audio from other domains such as drums, bird vocalizations, and piano.
Abstract: Audio signals are sampled at high temporal resolutions, and learning to synthesize audio requires capturing structure across a range of timescales. Generative adversarial networks (GANs) have seen wide success at generating images that are both locally and globally coherent, but they have seen little application to audio generation. In this paper we introduce WaveGAN, a first attempt at applying GANs to unsupervised synthesis of raw-waveform audio. WaveGAN is capable of synthesizing one second slices of audio waveforms with global coherence, suitable for sound effect generation. Our experiments demonstrate that, without labels, WaveGAN learns to produce intelligible words when trained on a small-vocabulary speech dataset, and can also synthesize audio from other domains such as drums, bird vocalizations, and piano. We compare WaveGAN to a method which applies GANs designed for image generation on image-like audio feature representations, finding both approaches to be promising.

246 citations

Proceedings ArticleDOI
01 Sep 2017
TL;DR: Experimental results demonstrate that adversarial training is generally effective for both CNN and RNN models and significantly improves the precision of predicted relations.
Abstract: Adversarial training is a mean of regularizing classification algorithms by generating adversarial noise to the training data. We apply adversarial training in relation extraction within the multi-instance multi-label learning framework. We evaluate various neural network architectures on two different datasets. Experimental results demonstrate that adversarial training is generally effective for both CNN and RNN models and significantly improves the precision of predicted relations.

246 citations

PatentDOI
TL;DR: In this article, an ion source utilizing a cathode and anode for producing an electric arc there between is described, where the arc is sufficient to vaporize a portion of the cathode to form a plasma.
Abstract: An ion source utilizing a cathode and anode for producing an electric arc therebetween. The arc is sufficient to vaporize a portion of the cathode to form a plasma. The plasma leaves the generation region and expands through another regon. The density profile of the plasma may be flattened using a magnetic field formed within a vacuum chamber. Ions are extracted from the plasma to produce a high current broad on beam.

246 citations

Book ChapterDOI
TL;DR: Population studies of genetic variation and microevolution are classically discussed in terms of changes in gene frequencies and the maintenance of polymorphic loci that can be identified by Mendelian analyses.
Abstract: Population studies of genetic variation and microevolution are classically discussed in terms of changes in gene frequencies and the maintenance of polymorphic loci that can be identified by Mendelian analyses. In recent years, however, a great deal of attention has been given to the evolutionary dynamics and polymorphisms of interacting and linked loci (e.g., Clegg et al., 1972; Lewontin, 1974; Karlin, 1976). The special properties of multilocus systems, namely, gene interaction and linkage, were first briefly considered in theory by Fisher (1930) and Wright (1932). Fisher discussed in particular the role of modifiers in the evolution of dominance and clearly recognized the importance of linkage in the evolution of interacting polymorphisms. Wright proposed an intermediate optimum model in which natural selection favors intermediate phenotypes over the extremes for a continuous metric trait and emphasized the role of linkage in the makeup of gametic arrays.

246 citations

Book ChapterDOI
09 Dec 2002
TL;DR: Ten principles for secure interaction design are identified and the concept of the subjective actor-ability state is introduced, to model systems in terms of actors and actions.
Abstract: The security of any system that is configured or operated by human beings depends on the information conveyed by the user interface, the decisions of the users, and the interpretation of their actions. This paper establishes some starting points for reasoning about security from a user-centred perspective: it proposes to model systems in terms of actors and actions, and introduces the concept of the subjective actor-ability state. Ten principles for secure interaction design are identified; examples of real-world problems illustrate and justify the principles.

245 citations


Authors

Showing all 55232 results

NameH-indexPapersCitations
Meir J. Stampfer2771414283776
George M. Whitesides2401739269833
Michael Karin236704226485
Fred H. Gage216967185732
Rob Knight2011061253207
Martin White1962038232387
Simon D. M. White189795231645
Scott M. Grundy187841231821
Peidong Yang183562144351
Patrick O. Brown183755200985
Michael G. Rosenfeld178504107707
George M. Church172900120514
David Haussler172488224960
Yang Yang1712644153049
Alan J. Heeger171913147492
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202322
2022105
2021775
20201,069
20191,225
20181,684