1,272 research outputs found
Insecurity Cameras: Cinematic Elevators, Infidelity and the Crime of Time
The elevator, like the train and other icons of automated movement, would seem to hold a natural affinity with cinema, a kind of machine for making non-habitual space and time. Elevators displace human activity and effort, opening up instead a range of other types of encounters and types of mobility. As time-based mediums, elevators are zones of duration where the potential for change is made manifest. Unlike trains, however, elevators have not received or drawn critical interest on the part of cinema studies. This paper looks at the enduring verticality of cinematic elevators through a Bergsonian sense of duration as “infidelity to the self”, presenting a close reading of the elevator murder in Brian DePalma’s Dressed to Kill (1980) and a broader consideration of the elevator in cinema and urban culture.À l’instar d’icônes du mouvement automatisé, comme le train, l’ascenseur semble présenter une affinité naturelle avec le cinéma dans la mesure où il crée un espace-temps non habituel. Les ascenseurs dévient les activités et les efforts humains, en déployant d’autres formes de mobilité et de rencontres. En tant que médiums temporels, les ascenseurs représentent des zones de durée où se manifeste explicitement un potentiel de changement. Mais, contrairement aux trains, les ascenseurs n’ont jamais fait l’objet d’études cinématographiques approfondies. Cet article se propose de penser l’axe vertical des ascenseurs cinématographiques à partir de la conception « bergsonnienne » de la durée comprise comme « infidélité à soi ». Le célèbre meurtre dans un ascenseur du film Dressed to Kill (1980) de Brian de Palma servira de point d’ancrage afin de mener cette étude sur le rôle de l’ascenseur au cinéma et dans la culture urbaine
SHADHO: Massively Scalable Hardware-Aware Distributed Hyperparameter Optimization
Computer vision is experiencing an AI renaissance, in which machine learning
models are expediting important breakthroughs in academic research and
commercial applications. Effectively training these models, however, is not
trivial due in part to hyperparameters: user-configured values that control a
model's ability to learn from data. Existing hyperparameter optimization
methods are highly parallel but make no effort to balance the search across
heterogeneous hardware or to prioritize searching high-impact spaces. In this
paper, we introduce a framework for massively Scalable Hardware-Aware
Distributed Hyperparameter Optimization (SHADHO). Our framework calculates the
relative complexity of each search space and monitors performance on the
learning task over all trials. These metrics are then used as heuristics to
assign hyperparameters to distributed workers based on their hardware. We first
demonstrate that our framework achieves double the throughput of a standard
distributed hyperparameter optimization framework by optimizing SVM for MNIST
using 150 distributed workers. We then conduct model search with SHADHO over
the course of one week using 74 GPUs across two compute clusters to optimize
U-Net for a cell segmentation task, discovering 515 models that achieve a lower
validation loss than standard U-Net.Comment: 10 pages, 6 figure
Credit Advertising and the Law: Truth in Lending and Related Matters
Whether full disclosure of credit terms will in fact improve the bargaining power of credit consumers is debatable. Borrowers may not be sophisticated enough to make effective use of the information disclosed and may not, in fact, have a choice of lenders. Furthermore, an applicant with a precarious credit status may care much less about locating favorable credit terms than about obtaining any credit. For these reasons, critics often decry Congress’ most recent legislation on credit advertising, the Truth-in-Lending Act, as “middle-class legislation.” Although categorized as “consumer protection legislation,” the Act offers little assistance to the consumers most in need of protection—those who have trouble obtaining credit on any terms
Developing and Communicating Better Sexual Harassment Policies Through Ethics and Human Rights
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