27,667 research outputs found

    Scalable Compression of Deep Neural Networks

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    Deep neural networks generally involve some layers with mil- lions of parameters, making them difficult to be deployed and updated on devices with limited resources such as mobile phones and other smart embedded systems. In this paper, we propose a scalable representation of the network parameters, so that different applications can select the most suitable bit rate of the network based on their own storage constraints. Moreover, when a device needs to upgrade to a high-rate network, the existing low-rate network can be reused, and only some incremental data are needed to be downloaded. We first hierarchically quantize the weights of a pre-trained deep neural network to enforce weight sharing. Next, we adaptively select the bits assigned to each layer given the total bit budget. After that, we retrain the network to fine-tune the quantized centroids. Experimental results show that our method can achieve scalable compression with graceful degradation in the performance.Comment: 5 pages, 4 figures, ACM Multimedia 201

    Double resonance in the infinite-range quantum Ising model

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    We study quantum resonance behavior of the infinite-range kinetic Ising model at zero temperature. Numerical integration of the time-dependent Schr\"odinger equation in the presence of an external magnetic field in the zz direction is performed at various transverse field strengths gg. It is revealed that two resonance peaks occur when the energy gap matches the external driving frequency at two distinct values of gg, one below and the other above the quantum phase transition. From the similar observations already made in classical systems with phase transitions, we propose that the double resonance peaks should be a generic feature of continuous transitions, for both quantum and classical many-body systems.Comment: 4 pages, 5 figure

    Lattice-coupled Antiferromagnet on Frustrated Lattices

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    Lattice-coupled antiferromagnetic spin model is analyzed for a number of frustrated lattices: triangular, Kagome, and pyrochlore. In triangular and Kagome lattices where ground state spins are locally ordered, the spin-lattice interaction does not lead to a static deformation of the lattice. In the pyrochlore structure, spin-lattice coupling supports a picture of the hexagon spin cluster proposed in the recent experiment[S. H. Lee et al. Nature, 418, 856 (2002)]. Through spin-lattice interaction a uniform contraction of the individual hexagons in the pyrochlore lattice can take place and reduce the exchange energy. Residual hexagon-hexagon interaction takes the form of a 3-states Potts model where the preferred directions of the spin-loop directors for nearby hexagons are mutually orthogonal

    MANDATORY VERSUS VOLUNTARY PRICE REPORTING: AN EMPIRICAL INVESTIGATION OF THE MARKET TRANSPARENCY CONTROVERSY

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    The ability of the former voluntary price reporting system to generate market transparency in U.S. livestock markets was called into question by producer groups and academic research prior to the new federal system of mandatory price reporting being implemented. The market transparency issue is investigated by comparing price data collected from the former AMS voluntary price reporting system to mandatory price reporting data for live slaughter steers collected by the State of South Dakota before the advent of the new federal system. The relationship between a set of public price report series and the South Dakota mandatory price series is analyzed using cointegration techniques. The empirical findings indicate a strong long-run and short-run integrated relationship between the mandatory price series and a majority of the selected public price reports. We conclude that in the cash market for live steers in South Dakota, the former voluntary price reporting system did foster market transparency and aided in the price discovery process.Marketing,

    Stokes Parameters as a Minkowskian Four-vector

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    It is noted that the Jones-matrix formalism for polarization optics is a six-parameter two-by-two representation of the Lorentz group. It is shown that the four independent Stokes parameters form a Minkowskian four-vector, just like the energy-momentum four-vector in special relativity. The optical filters are represented by four-by-four Lorentz-transformation matrices. This four-by-four formalism can deal with partial coherence described by the Stokes parameters. A four-by-four matrix formulation is given for decoherence effects on the Stokes parameters, and a possible experiment is proposed. It is shown also that this Lorentz-group formalism leads to optical filters with a symmetry property corresponding to that of two-dimensional Euclidean transformations.Comment: RevTeX, 22 pages, no figures, submitted to Phys. Rev.
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