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Fast Patch-based Style Transfer of Arbitrary Style
TLDR
We present a new CNN-based method of artistic style transfer that aims to be both fast and adaptable to arbitrary styles. Expand
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Graphical model structure learning using L₁-regularization
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Quantitative evaluation of 11C-ABP688 as PET ligand for the measurement of the metabotropic glutamate receptor subtype 5 using autoradiographic studies and a beta-scintillator
TLDR
In this study we assessed the new glutamatergic ligand (11)C-ABP688 with regard to the following characteristics: (A) brain distribution, (B) first pass extraction fraction, (C) suitable model to describe tracer kinetics and (D) specificity for mGlu5 receptor. Expand
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Real Democracy: The New England Town Meeting and How It Works
If you really want to be smarter, reading can be one of the lots ways to evoke and realize. Many people who like reading will have more knowledge and experiences. Reading can be a way to gainExpand
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Ju n 20 18 Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Lojasiewicz Condition
In 1963, Polyak proposed a simple condition that is sufficient to show a global linear convergence rate for gradient descent. This condition is a special case of the Lojasiewicz inequality proposedExpand
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Nonpotable Reuse: Development of Health Criteria and Technologies for Shower Water Recycle
The U.S. Army is evaluating recycle of field shower water as a conservation practice in arid regions and is seeking to define appropriate technologies and health criteria. Shower wastewaters at aExpand
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Let's Make Block Coordinate Descent Go Fast: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
Block coordinate descent (BCD) methods are widely-used for large-scale numerical optimization because of their cheap iteration costs, low memory requirements, amenability to parallelization, andExpand
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Play and Learn: Using Video Games to Train Computer Vision Models
TLDR
We present experiments assessing the effectiveness on real-world data of systems trained on synthetic RGB images that are extracted from a video game. Expand
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Model-Independent Online Learning for Influence Maximization
TLDR
We consider influence maximization (IM) in social networks, which is the problem of maximizing the number of users that become aware of a product by selecting a set of "seed" users. Expand
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Diffusion Independent Semi-Bandit Influence Maximization
TLDR
We propose a parametrization in terms of pairwise reachability which makes our framework agnostic to the underlying diffusion model and develop a LinUCB-based bandit algorithm. Expand
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