Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation

We study the problem of unsupervised domain adaptation, which aims to adapt classifiers trained on a labeled source domain to an unlabeled target domain. Many existing approaches first learn domain-invariant features and then construct classifiers with them. We propose a novel approach that jointly learn the both. Specifically, while the method identifies a feature space where data in the source and the target domains are similarly distributed, it also learns the feature space discriminatively, optimizing an information-theoretic metric as an proxy to the expected misclassification error on the target domain. We show how this optimization can be effectively carried out with simple gradient-based methods and how hyperparameters can be cross-validated without demanding any labeled data from the target domain. Empirical studies on benchmark tasks of object recognition and sentiment analysis validated our modeling assumptions and demonstrated significant improvement of our method over competing ones in classification accuracies.Comment: Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012

Correlated spontaneous symmetry breaking induced by zero-point fluctuations in a quantum mixture

We propose a form of spontaneous symmetry breaking driven by zero-point quantum fluctuations. To be specific, we consider the low-energy dynamics of a mixture of two species of spin-$1$ Bose gases. It is demonstrated that the quantum fluctuations lift a degeneracy regarding the relative orientations of the spin directors of the two species, and result in correlation or locking between these macroscopic variables. This locking persists in the presence of the trapping potential and weak magnetic fields, allowing, in principle, an experimental probe of this correlated spontaneous symmetry breaking, as a macroscopic manifestation of zero-point quantum fluctuations.Comment: 6 page

Off-diagonal Long-Range Order and Supersolidity in a Quantum Solid with Vacancies

We consider a lattice of bosonic atoms, whose number N may be smaller than the number of lattice sites M. We study the Hartree-Fock wave function built up from localized wave functios w(\mathbf{r}) of single atoms, with nearest neighboring overlap. The zero-momentum particle number is expressed in terms of permanents of matrices. In one dimension, it is analytically calculated to be \alpha*N(M-N+1)/M, with \alpha=|\int w(\mathbf{r})d\Omega|^2/[(1+2a)l], where a is the nearest-neighboring overlap, l is the lattice constant. \alpha is of the order of 1. The result indicates that the condensate fraction is proportional to and of the same order of magnitude as that of the vacancy concentration, hence there is off-diagonal long-range order or Bose-Einstein condensation of atoms when the number of vacancies M-N is a finite fraction of the number of the lattice sites M.Comment: 12 pages. A few references are added. To appear in PR

CHY formula and MHV amplitudes

In this paper, we study the relation between the Cachazo-He-Yuan (CHY) formula and the maximal-helicity-violating (MHV) amplitudes of Yang-Mills and gravity in four dimensions. We prove that only one special rational solution of the scattering equations found by Weinzierl support the MHV amplitudes. Namely, localized at this solution, the integrated CHY formula reproduces the Parke-Taylor formula for Yang-Mills amplitudes as well as the Hodges formula for gravitational amplitudes. This is achieved by developing techniques, in a manifestly M\"obius covariant formalism, to explicitly compute relevant reduced Pfaffians/determinants. We observe and prove two interesting properties (or identities), which facilitate the computations. We also check that all the other $(n-3)!-1$ solutions to the scattering equations do not support the MHV amplitudes, and prove analytically that this is indeed true for the other special rational solution proposed by Weinzierl, that actually supports the anti-MHV amplitudes.Comment: 28 pages, 4 figures, published versio

A resnet-based universal method for speckle reduction in optical coherence tomography images

In this work we propose a ResNet-based universal method for speckle reduction in optical coherence tomography (OCT) images. The proposed model contains 3 main modules: Convolution-BN-ReLU, Branch and Residual module. Unlike traditional algorithms, the model can learn from training data instead of selecting parameters manually such as noise level. Application of this proposed method to the OCT images shows a more than 22 dB signal-to-noise ratio improvement in speckle noise reduction with minimal structure blurring. The proposed method provides strong generalization ability and can process noisy other types of OCT images without retraining. It outperforms other filtering methods in suppressing speckle noises and revealing subtle features

Efficient Simulation Budget Allocation for Subset Selection Using Regression Metamodels

This research considers the ranking and selection (R&S) problem of selecting the optimal subset from a finite set of alternative designs. Given the total simulation budget constraint, we aim to maximize the probability of correctly selecting the top-m designs. In order to improve the selection efficiency, we incorporate the information from across the domain into regression metamodels. In this research, we assume that the mean performance of each design is approximately quadratic. To achieve a better fit of this model, we divide the solution space into adjacent partitions such that the quadratic assumption can be satisfied within each partition. Using the large deviation theory, we propose an approximately optimal simulation budget allocation rule in the presence of partitioned domains. Numerical experiments demonstrate that our approach can enhance the simulation efficiency significantly

Metaflow: A DAG-Based Network Abstraction for Distributed Applications

In the past decade, increasingly network scheduling techniques have been proposed to boost the distributed application performance. Flow-level metrics, such as flow completion time (FCT), are based on the abstraction of flows yet they cannot capture the semantics of communication in a cluster application. Being aware of this problem, coflow is proposed as a new network abstraction. However, it is insufficient to reveal the dependencies between computation and communication. As a result, the real application performance can be hurt, especially in the absence of hard barriers. Based on the computation DAG of the application, we propose an expressive abstraction namely metaflow that resides in the middle of the two extreme points of flows and coflows. Evaluation results show that metaflow-based scheduling can outperform the coflow-based algorithm by 1.78x

Transport evidence for the coexistence of the topological surface state and a two-dimensional electron gas in BiSbTe3 topological insulator

Topological insulators (TIs) are new insulating materials with exotic surface states, where the motion of charge carriers is described by the Dirac equations and their spins are locked in a perpendicular direction to their momentum. Recent studies by angle-resolved photoemission spectroscopy have demonstrated that a conventional two-dimensional electron gas can coexist with the topological surface state due to the quantum confinement effect. The coexistence is expected to give rise to exotic transport properties, which, however, have not been explored so far. Here, we report a magneto-transport study on single crystals of the topological insulator BiSbTe3. Besides Shubnikov-de Haas oscillations and weak anti-localization (WAL) from the topological surface state, we also observed a crossover from the weak anti-localization to weak localization (WL) with increasing magnetic field, which is temperature dependent and exhibits two-dimensional features. The crossover is proposed to be the transport manifestation of the coexistence of the topological surface state and two-dimensional electron gas on the surface of TIs.Comment: 11 pages, 4 figure

Crossover from a continuum study of chiral susceptibility

We derive a model-independent integral formula for chiral susceptibility and attempt to present a continuum model study of it within the framework of Dyson-Schwinger Equations. An appropriate regularization is implemented to remove the temperature-independent quadratic divergence inherent in this quantity. While it demonstrates a second-order phase transition characteristic in the chiral limit, the result obtained supports a crossover at physical current quark masses, which is in good agreement with recent lattice studies.Comment: 15 pages, 2 figures, revtex

Experimental test of Heisenberg's measurement uncertainty relation based on statistical distances

Incompatible observables can be approximated by compatible observables in joint measurement or measured sequentially, with constrained accuracy as implied by Heisenberg's original formulation of the uncertainty principle. Recently, Busch, Lahti, and Werner proposed inaccuracy trade-off relations based on statistical distances between probability distributions of measurement outcomes [Phys. Rev. Lett. 111, 160405 (2013); Phys. Rev. A 89, 012129 (2014)]. Here we reform their theoretical framework, derive an improved relation for qubit measurement, and perform an experimental test on a spin system. The relation reveals that the worst-case inaccuracy is tightly bounded from below by the incompatibility of target observables, and is verified by the experiment employing joint measurement in which two compatible but typically non-commutative observables on one qubit are measured simultaneously