Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors

Object detection aims at high speed and accuracy simultaneously. However, fast models are usually less accurate, while accurate models cannot satisfy our need for speed. A fast model can be 10 times faster but 50\% less accurate than an accurate model. In this paper, we propose Adaptive Feeding (AF) to combine a fast (but less accurate) detector and an accurate (but slow) detector, by adaptively determining whether an image is easy or hard and choosing an appropriate detector for it. In practice, we build a cascade of detectors, including the AF classifier which make the easy vs. hard decision and the two detectors. The AF classifier can be tuned to obtain different tradeoff between speed and accuracy, which has negligible training time and requires no additional training data. Experimental results on the PASCAL VOC, MS COCO and Caltech Pedestrian datasets confirm that AF has the ability to achieve comparable speed as the fast detector and comparable accuracy as the accurate one at the same time. As an example, by combining the fast SSD300 with the accurate SSD500 detector, AF leads to 50\% speedup over SSD500 with the same precision on the VOC2007 test set.Comment: To appear in ICCV 201

Quadrupole Plasmon Excitations in Confined One-dimensional Systems

The existence and nature of a new mode of electronic collective excitations (quadrupole plasmons) in confined one-dimensional electronic systems have been predicted by an eigen-equation method. The eigen-equation based on the time-dependent density-functional theory is presented for calculating the collective excitations in confined systems. With this method, all modes of collective excitations in the 1D systems may be found out. These modes include dipole plasmons and quadrupole plasmons. The dipole plasmon mode corresponds to the antisymmetric oscillation of induced charge, and can be shown as a resonance of the dipole response. In the quadrupole plasmon modes, the induced charge distribution is symmetric, and the dipole response vanishes. The motion of the electrons in the quadrupole modes is similar to the vibration of atoms in the breathing mode of phonons. This type of plasmons can be shown as a resonance of the quadrupole response, and has to be excited by al non-uniform field

Poincar\'e-De Sitter Flow and Cosmological Meaning

We introduce the Poincar\'e-de Sitter flow with real numbers $\{r,s\}$ to parameterize the relativistic quadruple ${\frak Q}_{PoR}=[{\cal P}, {\cal P}_2, {\cal D}_+,{\cal D}_-]_{M/M_\pm/D_\pm}$ for the triple of Poincar\'e/\dS/\AdS\ group ${\cal P}/{\cal D}_+/{\cal D}_-$ invariant special relativity. The dual Poincar\'e group ${\cal P}_2$-invariant degenerated Einstein manifold $M_\pm$ of $\Lambda_\pm=\pm3l^{-2}$ is for the space/time-like domain $\dot R_\pm$ of the compact lightcone $\bar C_O$ associated to the common space/time-like region $R_\pm$ of the lightcone $C_O$ at common origin on Minkowski/\dS/\AdS\ spacetime $M/D_+/D_-$. Based on the principle of relativity with two universal constants $(c, l)$, there are the law of inertia, coordinate time simultaneity and so on for the flow on a Poincar\'e-\dS\ symmetric Einstein manifold of $\Lambda_{s}=3{s}l^{-2}$. Further, there is Robertson-Walker-like cosmos of the flow for the propertime simultaneity. The \dS\ special relativity with double $[{\cal D}_+,{\cal P}_2]_{D_+/M_+}$ can provide a consistent kinematics for the cosmic scale physics with an upper entropy bound $S_R=k_B\pi g^{-2}, g^2:=(\ell_P/R)^2 \simeq 10^{-122}$, for $R\simeq (3/\Lambda)^{1/2}\sim 13.7 Gly$.Comment: 25 page

Vortex Pooling: Improving Context Representation in Semantic Segmentation

Semantic segmentation is a fundamental task in computer vision, which can be considered as a per-pixel classification problem. Recently, although fully convolutional neural network (FCN) based approaches have made remarkable progress in such task, aggregating local and contextual information in convolutional feature maps is still a challenging problem. In this paper, we argue that, when predicting the category of a given pixel, the regions close to the target are more important than those far from it. To tackle this problem, we then propose an effective yet efficient approach named Vortex Pooling to effectively utilize contextual information. Empirical studies are also provided to validate the effectiveness of the proposed method. To be specific, our approach outperforms the previous state-of-the-art model named DeepLab v3 by 1.5% on the PASCAL VOC 2012 val set and 0.6% on the test set by replacing the Atrous Spatial Pyramid Pooling (ASPP) module in DeepLab v3 with the proposed Vortex Pooling. Moreover, our model (10.13FPS) shares similar computation cost with DeepLab v3 (10.37 FPS)

A possible resolution of tension between {\it Planck} and Type Ia supernova observations

There is an apparent tension between cosmological parameters obtained from {\it Planck} cosmic microwave background radiation observations and that derived from the observed magnitude-redshift relation for the type Ia supernova (SNe Ia). Here, we show that the tension can be alleviated, if we first calibrate, with the help of the distance-duality relation, the light-curve fitting parameters in the distance estimation in SNe Ia observations with the angular diameter distance data of the galaxy clusters and then re-estimate the distances for the SNe Ia with the corrected fitting parameters. This was used to explore their cosmological implications in the context of the spatially flat cosmology. We find a higher value for the matter density parameter, $\Omega_m$, as compared to that from the original SNLS3, which is in agreement with {\it Planck} observations at $68.3\%$ confidence. Therefore, the tension between {\it Planck} measurements and SNe Ia observations regarding $\Omega_m$ can be effectively alleviated without invoking new physics or resorting to extensions for the standard concordance model. Moreover, with the absolute magnitude of a fiducial SNe Ia, $M$, determined first, we obtained a constraint on the Hubble constant with SNLS3 alone, which is also consistent with {\it Planck}.Comment: 12 pages, 3 figures, matches the vershion to be published in Science in China Series

When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets

Semi-Supervised Learning (SSL) has been proved to be an effective way to leverage both labeled and unlabeled data at the same time. Recent semi-supervised approaches focus on deep neural networks and have achieved promising results on several benchmarks: CIFAR10, CIFAR100 and SVHN. However, most of their experiments are based on models trained from scratch instead of pre-trained models. On the other hand, transfer learning has demonstrated its value when the target domain has limited labeled data. Here comes the intuitive question: is it possible to incorporate SSL when fine-tuning a pre-trained model? We comprehensively study how SSL methods starting from pretrained models perform under varying conditions, including training strategies, architecture choice and datasets. From this study, we obtain several interesting and useful observations. While practitioners have had an intuitive understanding of these observations, we do a comprehensive emperical analysis and demonstrate that: (1) the gains from SSL techniques over a fully-supervised baseline are smaller when trained from a pre-trained model than when trained from random initialization, (2) when the domain of the source data used to train the pre-trained model differs significantly from the domain of the target task, the gains from SSL are significantly higher and (3) some SSL methods are able to advance fully-supervised baselines (like Pseudo-Label). We hope our studies can deepen the understanding of SSL research and facilitate the process of developing more effective SSL methods to utilize pre-trained models. Code is now available at github.Comment: Technical repor

Code Attention: Translating Code to Comments by Exploiting Domain Features

Appropriate comments of code snippets provide insight for code functionality, which are helpful for program comprehension. However, due to the great cost of authoring with the comments, many code projects do not contain adequate comments. Automatic comment generation techniques have been proposed to generate comments from pieces of code in order to alleviate the human efforts in annotating the code. Most existing approaches attempt to exploit certain correlations (usually manually given) between code and generated comments, which could be easily violated if the coding patterns change and hence the performance of comment generation declines. In this paper, we first build C2CGit, a large dataset from open projects in GitHub, which is more than 20$\times$ larger than existing datasets. Then we propose a new attention module called Code Attention to translate code to comments, which is able to utilize the domain features of code snippets, such as symbols and identifiers. We make ablation studies to determine effects of different parts in Code Attention. Experimental results demonstrate that the proposed module has better performance over existing approaches in both BLEU and METEOR

Implications of the first AMS-02 measurement for dark matter annihilation and decay

In light of the first measurement of the positron fraction by the AMS-02 experiment, we perform a detailed global analysis on the interpretation of the latest data of PAMELA, Fermi-LAT, and AMS-02 in terms of dark matter (DM) annihilation and decay in various propagation models. The allowed regions for the DM particle mass and annihilation cross section or decay life-time are obtained for channels with leptonic final states: $2e$, $2\mu$, $2\tau$, $4e$, $4\mu$ and $4\tau$. We show that for the conventional astrophysical background the AMS-02 positron fraction data alone favour a DM particle mass $\sim 500 \ (800)$GeV if DM particles annihilate dominantly into$2\mu \ (4\mu)$final states, which is significantly lower than that favoured by the Fermi-LAT data of the total flux of electrons and positrons. The allowed regions by the two experiments do not overlap at a high confidence level ($99.99999\%$C.L.). We consider a number of propagation models with different halo height$Z_{h}$, diffusion parameters$D_{0}$and$\delta_{1/2}$, and power indices of primary nucleon sources$\gamma_{p1/p2}$. The normalization and the slope of the electron background are also allowed to vary. We find that the tension between the two experiments can be only slightly reduced in the propagation model with large$Z_{h}$and$D_{0}$. The consistency of fit is improved for annihilation channels with$2\tau$and$4\tau$final states which favour TeV scale DM particle with large cross sections above$\sim 10^{-23} \text{cm}^3\text{s}^{-1}$. In all the considered leptonic channels, the current data favour the scenario of DM annihilation over DM decay. In the decay scenario, the charge asymmetric DM decay is slightly favoured.Comment: 27 pages, 12 figures, 3 tables, in-depth discussions on the uncertainties in backgrounds and propagation models added, version to appear in JCA

Implications of the first AMS-02 antiproton data for dark matter

The implications of the first AMS-02 $\bar p/p$ data for the propagation of cosmic rays and the properties of dark matter (DM) are discussed. Using various diffusive re-acceleration (DR) propagation models, one can derive very conservative upper limits on the DM annihilation cross sections. The limits turned out to be compatible with that from the Ferm-LAT gamma-ray data on the dwarf spheroidal satellite galaxies. The flattening of the $\bar p/p$ spectrum above $\sim 100$~GeV in the current data still leaves some room for TeV scale DM particles. More antiproton data at high kinetic energies are needed to constrain the properties of the DM particles.Comment: Talk given at the International Conference on Gravitation and Cosmology, May 5-8, 2015, Beijing, to appear in the proceeding

Electrical Control of Strong Spin-Phonon Coupling in a Carbon Nanotube

We describe an approach to electrically control the strong interaction between a single electron spin and the vibrational motion of a suspended carbon nanotube resonator. The strength of the deflection-induced spin-phonon coupling is dependent on the wavefunction of the electron confined in a lateral carbon nanotube quantum dot. An electrical field along the nanotube shifts the effective center of the quantum dot, leading to the corresponding modification of the spin-phonon strength. Numerical simulations with experimentally reachable parameters show that high fidelity quantum state transfer between mechanical and spin qubits driven by electrical pulses is feasible. Our results form the basis for the fully electrical control of the coherent interconvertion between light and spin qubits and for manufacturing electrically driven quantum information processing systems.Comment: 4pages,3figure