Xin Jiang

Xin Jiang
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Xin Jiang
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Physics - Materials Science (4)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (3)
 
Computer Science - Information Theory (3)
 
Mathematics - Information Theory (3)
 
Nonlinear Sciences - Adaptation and Self-Organizing Systems (2)
 
Mathematics - Statistics (2)
 
Computer Science - Computation and Language (2)
 
Physics - Other (2)
 
Statistics - Theory (2)
 
Physics - Physics and Society (2)
 
General Relativity and Quantum Cosmology (1)
 
Statistics - Applications (1)
 
Nonlinear Sciences - Chaotic Dynamics (1)
 
Computer Science - Neural and Evolutionary Computing (1)
 
Computer Science - Artificial Intelligence (1)
 
Physics - Soft Condensed Matter (1)
 
Statistics - Machine Learning (1)
 
Nonlinear Sciences - Pattern Formation and Solitons (1)
 
Computer Science - Learning (1)
 
Computer Science - Information Retrieval (1)

Publications Authored By Xin Jiang

To improve national security, government agencies have long been committed to enforcing powerful surveillance measures on suspicious individuals or communications. In this paper, we consider a wireless legitimate surveillance system, where a full-duplex multi-antenna legitimate monitor aims to eavesdrop on a dubious communication link between a suspicious pair via proactive jamming. Assuming that the legitimate monitor can successfully overhear the suspicious information only when its achievable data rate is no smaller than that of the suspicious receiver, the key objective is to maximize the eavesdropping non-outage probability by joint design of the jamming power, receive and transmit beamformers at the legitimate monitor. Read More

This paper investigates the performance of a legitimate surveillance system, where a legitimate monitor aims to eavesdrop on a dubious decode-and-forward relaying communication link. In order to maximize the effective eavesdropping rate, two strategies are proposed, where the legitimate monitor adaptively acts as an eavesdropper, a jammer or a helper. In addition, the corresponding optimal jamming beamformer and jamming power are presented. Read More

We propose an online, end-to-end, neural generative conversational model for open-domain dialog. It is trained using a unique combination of offline two-phase supervised learning and online human-in-the-loop active learning. While most existing research proposes offline supervision or hand-crafted reward functions for online reinforcement, we devise a novel interactive learning mechanism based on a diversity-promoting heuristic for response generation and one-character user-feedback at each step. Read More

We investigate how thin structures change their shape in response to non-mechanical stimuli that can be interpreted as variations in the structure's natural curvature. Starting from the theory of non-Euclidean plates and shells, we derive an effective model that reduces a three-dimensional stimulus to the natural fundamental forms of the mid-surface of the structure, incorporating expansion, or growth, in the thickness. Then, we apply the model to a variety of thin bodies, from flat plates to spherical shells, obtaining excellent agreement between theory and numerics. Read More

In an era of ubiquitous large-scale streaming data, the availability of data far exceeds the capacity of expert human analysts. In many settings, such data is either discarded or stored unprocessed in datacenters. This paper proposes a method of online data thinning, in which large-scale streaming datasets are winnowed to preserve unique, anomalous, or salient elements for timely expert analysis. Read More

When identical oscillators are coupled together in a network, dynamical steady states are often assumed to reflect network symmetries. Here we show that alternative persistent states may also exist that break the symmetries of the underlying coupling network. We further show that these symmetry-broken coexistent states are analogous to those dubbed "chimera states," which can occur when identical oscillators are coupled to one another in identical ways. Read More

Financial markets have been extensively studied as highly complex evolving systems. In this paper, we quantify financial price fluctuations through a coupled dynamical system composed of phase oscillators. We find a Financial Coherence and Incoherence (FCI) coexistence collective behavior emerges as the system evolves into the stable state, in which the stocks split into two groups: one is represented by coherent, phase-locked oscillators, the other is composed of incoherent, drifting oscillators. Read More

The relevance between a query and a document in search can be represented as matching degree between the two objects. Latent space models have been proven to be effective for the task, which are often trained with click-through data. One technical challenge with the approach is that it is hard to train a model for tail queries and tail documents for which there are not enough clicks. Read More

The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. Read More

This paper presents an end-to-end neural network model, named Neural Generative Question Answering (GENQA), that can generate answers to simple factoid questions, based on the facts in a knowledge-base. More specifically, the model is built on the encoder-decoder framework for sequence-to-sequence learning, while equipped with the ability to enquire the knowledge-base, and is trained on a corpus of question-answer pairs, with their associated triples in the knowledge-base. Empirical study shows the proposed model can effectively deal with the variations of questions and answers, and generate right and natural answers by referring to the facts in the knowledge-base. Read More

Sparse linear inverse problems appear in a variety of settings, but often the noise contaminating observations cannot accurately be described as bounded by or arising from a Gaussian distribution. Poisson observations in particular are a characteristic feature of several real-world applications. Previous work on sparse Poisson inverse problems encountered several limiting technical hurdles. Read More

The spin Hall effect (SHE) converts charge current to pure spin currents in orthogonal directions in materials that have significant spin-orbit coupling.The efficiency of the conversion is described by the spin Hall Angle (SHA). The SHA can most readily be inferred by using the generated spin currents to excite or rotate the magnetization of ferromagnetic films or nano-elements via spin-transfer torques. Read More

Aiming at a unified phase transition picture of the charged topological black hole in Ho\v{r}ava-Lifshitz gravity, we investigate this issue not only in canonical ensemble with the fixed charge case but also in grand-canonical ensemble with the fixed potential case. We firstly perform the standard analysis of the specific heat, the free energy and the Gibbs potential, and then study its geometrothermodynamics. It is shown that the local phase transition points not only witness the divergence of the specific heat, but also witness the minimum temperature and the maximum free energy or Gibbs potential. Read More

This paper considers fundamental limits for solving sparse inverse problems in the presence of Poisson noise with physical constraints. Such problems arise in a variety of applications, including photon-limited imaging systems based on compressed sensing. Most prior theoretical results in compressed sensing and related inverse problems apply to idealized settings where the noise is i. Read More

The contact mechanics of individual, very small particles with other particles and walls is studied using a nanoindenter setup that allows normal and lateral displacement control and measurement of the respective forces. The sliding, rolling and torsional forces and torques are tested with borosilicate microspheres, featuring radii of about 10$\mu$m. The contacts are with flat silicon substrates of different roughness for pure sliding and rolling and with silicon based, ion-beam crafted rail systems for combined rolling and torsion. Read More

There has been much interest in the injection and detection of spin polarized carriers in semiconductors for the purposes of developing novel spintronic devices. Here we report the electrical injection and detection of spin-polarized carriers into Nb-doped strontium titanate (STO) single crystals and La-doped STO epitaxial thin films using MgO tunnel barriers and the three-terminal Hanle technique. Spin lifetimes of up to ~100 ps are measured at room temperature and vary little as the temperature is decreased to low temperatures. Read More

Atmospheric aerosols can cause serious damage to human health and life expectancy. Using the radiances observed by NASA's Multi-angle Imaging SpectroRadiometer (MISR), the current MISR operational algorithm retrieves Aerosol Optical Depth (AOD) at a spatial resolution of 17.6 km x 17. Read More

Thermal-magnetic noise at ferromagnetic resonance (T-FMR) can be used to measure magnetic perpendicular anisotropy of nanoscale magnetic tunnel junctions (MTJs). For this purpose, T-FMR measurements were conducted with an external magnetic field up to 14 kOe applied perpendicular to the film surface of MgO-based MTJs under a dc bias. The observed frequency-field relationship suggests that a 20 A CoFeB free layer has an effective demagnetization field much smaller than the intrinsic bulk value of CoFeB, with 4PiMeff = (6. Read More

We introduce a non-interacting boson model to investigate topological structure of complex networks in the present paper. By exactly solving this model, we show that it provides a powerful analytical tool in uncovering the important properties of real-world networks. We find that the ground state degeneracy of this model is equal to the number of connected components in the network and the square of coefficients in the expansion of ground state gives the averaged time for a random walker spending at each node in the infinite time limit. Read More

A simple model is proposed to simulate the evolution of interpersonal relationships in a class. The small social network is simply assumed as an undirected and weighted graph, in which students are represented by vertices, and the extent of favor or disfavor between two of them are denoted by the weight of corresponding edge. Various weight distributions have been found by choosing different initial configurations. Read More

A model has been proposed to simulate the evolution of interpersonal relationships in a social group. The small social community is simply assumed as an undirected and weighted graph, where individuals are denoted by vertices, and the extent of favor or disfavor between them are represented by the corresponding edge weight. One could further define the strength of vertices to describe the individual popularity. Read More