10,577 research outputs found

    Resource Constrained Structured Prediction

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    We study the problem of structured prediction under test-time budget constraints. We propose a novel approach applicable to a wide range of structured prediction problems in computer vision and natural language processing. Our approach seeks to adaptively generate computationally costly features during test-time in order to reduce the computational cost of prediction while maintaining prediction performance. We show that training the adaptive feature generation system can be reduced to a series of structured learning problems, resulting in efficient training using existing structured learning algorithms. This framework provides theoretical justification for several existing heuristic approaches found in literature. We evaluate our proposed adaptive system on two structured prediction tasks, optical character recognition (OCR) and dependency parsing and show strong performance in reduction of the feature costs without degrading accuracy

    The \u27Nayirah\u27 Effect: The Role of Target States’ Human Rights Violations and Victims’ Emotive Images in War Support

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    When a target state violates human rights, how does the identity of the victims and the presence of emotive imagery affect the level of public support for interventionist war? How does the perceived race and gender of victims affect this relationship? We employ a survey experiment to study whether and when information about a target state’s human rights violations affects public attitudes toward the use of force. Specifically, we manipulate a fictional victim’s race (light-skinned vs. dark-skinned) and gender (male vs. female), and explore how these variations affect support for interventionist war. In our experiment, we find that war support is stronger when a target state violates human rights. More importantly, public support for intervention was affected by the characteristics of the victims of human rights abuse. Support for interventionist war was found to be greatest among those participants who viewed images of light-skinned or female victims, though a white male image was found to me most impactful. Our causal mediation analysis showed that subjects viewing light-skinned or female images had less concern about the costs of intervention. Our findings suggest that the racial and gender characteristics of the victims of human rights abuse plays a substantial role in determining individual support for war
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