arXiv subjects

Yan Liang

Publications and source records attributed to Yan Liang.

89 records · Page 5Linked to original sources

arXiv2020

Kepler-90: Giant transit-timing variations reveal a super-puff

Exoplanet Transit Timing Variations (TTVs) caused by gravitational forces between planets can be used to determine planetary masses and orbital parameters. Most of the observed TTVs are small and sinusoidal in time, leading to degeneracies between the masses and orbital parameters. Here we report a TTV analysis of Kepler-90g and Kepler-90h, which exhibit large TTVs up to 25 hours. With optimization, we find a unique solution which allows us to constrain all of the orbital parameters. The best fit masses for Kepler-90g and 90h are $15.0^{+0.9}_{-0.8}$ $M_{\bigoplus}$ (Earth mass) and $203^{+5}_{-5}M_{\bigoplus}$, respectively, with Kepler-90g having an unusually low apparent density of $0.15\pm 0.05\, {\rm g\,cm^{-3}}$. The uniqueness of orbital parameter solution enables a long-term dynamical integration, which reveals that although their periods are close to 2:3 orbital resonance, they are not locked in resonance, and the configuration is stable over billions of years. The dynamical history of the system suggests that planet interactions are able to raise the eccentricities and break the resonant lock after the initial formation.

astro-ph.EP↗

arXiv2020

AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

Can one build a knowledge graph (KG) for all products in the world? Knowledge graphs have firmly established themselves as valuable sources of information for search and question answering, and it is natural to wonder if a KG can contain information about products offered at online retail sites. There have been several successful examples of generic KGs, but organizing information about products poses many additional challenges, including sparsity and noise of structured data for products, complexity of the domain with millions of product types and thousands of attributes, heterogeneity across large number of categories, as well as large and constantly growing number of products. We describe AutoKnow, our automatic (self-driving) system that addresses these challenges. The system includes a suite of novel techniques for taxonomy construction, product property identification, knowledge extraction, anomaly detection, and synonym discovery. AutoKnow is (a) automatic, requiring little human intervention, (b) multi-scalable, scalable in multiple dimensions (many domains, many products, and many attributes), and (c) integrative, exploiting rich customer behavior logs. AutoKnow has been operational in collecting product knowledge for over 11K product types.

cs.AI↗

arXiv2019

Bifrequency 3D Ghost Imaging with Haar Wavelet Transform

Recently, ghost imaging has been attracting attentions because its mechanism would lead to many applications inaccessible to conventional imaging methods. However, it is challenging for high contrast and high resolution imaging, due to its low signal-to-noise ratio (SNR) and the demand of high sampling rate in detection. To circumvent these challenges, we here propose a ghost imaging scheme that exploits Haar wavelets as illuminating patterns with a bi-frequency light projecting system and frequency-selecting single-pixel detectors. This method provides a theoretically 100% image contrast and high detection SNR, which reduces the requirement of high dynamic range of detectors, enabling high resolution ghost imaging. Moreover, it can highly reduce the sampling rate (far below Nyquist limit) for a sparse object by adaptively abandoning unnecessary patterns during the measurement. These characteristics are experimentally verified with a resolution of 512 times 512 and a sampling rate lower than 5%. A high-resolution (1000 times 1000 times 1000) 3D reconstruction of an object is also achieved from multi-angle images.

eess.IV↗

arXiv2019

Fatou's Lemma in Its Classic Form and Lebesgue's Convergence Theorems for Varying Measures with Applications to MDPs

The classic Fatou lemma states that the lower limit of a sequence of integrals of functions is greater or equal than the integral of the lower limit. It is known that Fatou's lemma for a sequence of weakly converging measures states a weaker inequality because the integral of the lower limit is replaced with the integral of the lower limit in two parameters, where the second parameter is the argument of the functions. This paper provides sufficient conditions when Fatou's lemma holds in its classic form for a sequence of weakly converging measures. The functions can take both positive and negative values. The paper also provides similar results for sequences of setwise converging measures. It also provides Lebesgue's and monotone convergence theorems for sequences of weakly and setwise converging measures. The obtained results are used to prove broad sufficient conditions for the validity of optimality equations for average-cost Markov decision processes.

math.PR↗

arXiv2019

Relation Discovery with Out-of-Relation Knowledge Base as Supervision

Unsupervised relation discovery aims to discover new relations from a given text corpus without annotated data. However, it does not consider existing human annotated knowledge bases even when they are relevant to the relations to be discovered. In this paper, we study the problem of how to use out-of-relation knowledge bases to supervise the discovery of unseen relations, where out-of-relation means that relations to discover from the text corpus and those in knowledge bases are not overlapped. We construct a set of constraints between entity pairs based on the knowledge base embedding and then incorporate constraints into the relation discovery by a variational auto-encoder based algorithm. Experiments show that our new approach can improve the state-of-the-art relation discovery performance by a large margin.

cs.CL↗

arXiv2019

Fatou's Lemma for Weakly Converging Measures under the Uniform Integrability Condition

This note describes Fatou's lemma and Lebesgue's dominated convergence theorem for a sequence of measures converging weakly to a finite measure and for a sequence of functions whose negative parts are uniformly integrable with respect to these measures. The note also provides new formulations of uniform Fatou's lemma, uniform Lebesgue convergence theorem, the Dunford-Pettis theorem, and the fundamental theorem for Young measures based on the equivalence of uniform integrability and the apparently weaker property of asymptotic uniform integrability for sequences of functions and finite measures.

math.CA↗

arXiv2017

Formalizing Interruptible Algorithms for Human over-the-loop Analytics

Traditional data mining algorithms are exceptional at seeing patterns in data that humans cannot, but are often confused by details that are obvious to the organic eye. Algorithms that include humans "in-the-loop" have proved beneficial for accuracy by allowing a user to provide direction in these situations, but the slowness of human interactions causes execution times to increase exponentially. Thus, we seek to formalize frameworks that include humans "over-the-loop", giving the user an option to intervene when they deem it necessary while not having user feedback be an execution requirement. With this strategy, we hope to increase the accuracy of solutions with minimal losses in execution time. This paper describes our vision of this strategy and associated problems.

cs.HC↗

arXiv2017

Stochastic Setup-Cost Inventory Model with Backorders and Quasiconvex Cost Functions

In this paper we study a periodic-review single-commodity setup-cost inventory model with backorders and holding/backlog costs satisfying quasiconvexity assumptions. We show that the Markov decision process for this inventory model satisfies the assumptions that lead to the validity of optimality equations for discounted and average-cost problems and to the existence of optimal $(s,S)$ policies. In particular, we prove the equicontinuity of the family of discounted value functions and the convergence of optimal discounted lower thresholds to the optimal average-cost one for some sequences of discount factors converging to $1.$ If an arbitrary nonnegative amount of inventory can be ordered, we establish stronger convergence properties: (i) the optimal discounted lower thresholds $s_α$ converge to optimal average-cost lower threshold $s;$ and (ii) the discounted relative value functions converge to average-cost relative value function. These convergence results previously were known only for subsequences of discount factors even for problems with convex holding/backlog costs. The results of this paper hold for problems with deterministic positive lead times.

math.OC↗

arXiv2017

Structure of Optimal Solutions to Periodic-Review Total-Cost Inventory Control Models with Convex Costs and Backorders for all Values of Discount Factors

This paper describes the structure of optimal policies for discounted periodic-review single-commodity total-cost inventory control problems with fixed ordering costs for finite and infinite horizons. There are known conditions in the literature for optimality of $(s_t,S_t)$ policies for finite-horizon problems and the optimality of $(s,S)$ policies for infinite-horizon problems. The results of this paper cover the situation, when such assumption may not hold. This paper describes a parameter, which, together with the value of the discount factor and the horizon length, defines the structure of an optimal policy. For the infinite horizon, depending on the values of this parameter and the discount factor, an optimal policy either is an $(s,S)$ policy or never orders inventory. For a finite horizon, depending on the values of this parameter, the discount factor, and the horizon length, there are three possible structures of an optimal policy: (i) it is an $(s_t,S_t)$ policy, (ii) it is an $(s_t,S_t)$ policy at earlier stages and then does not order inventory, or (iii) it never orders inventory. The paper also establishes continuity of optimal value functions and describes alternative optimal actions at states $s_t$ and $s.$

math.OC↗

arXiv2016

On the Optimality Equation for Average Cost Markov Decision Processes and its Validity for Inventory Control

As is well known, average-cost optimality inequalities imply the existence of stationary optimal policies for Markov Decision Processes with average costs per unit time, and these inequalities hold under broad natural conditions. This paper provides sufficient conditions for the validity of the average-cost optimality equation for an infinite state problem with weakly continuous transition probabilities and with possibly unbounded one-step costs and noncompact action sets. These conditions also imply the convergence of sequences of discounted relative value functions to average-cost relative value functions and the continuity of average-cost relative value functions. As shown in the paper, the classic periodic-review inventory control problem satisfies these conditions. Therefore, the optimality inequality holds in the form of an equality with a continuous average-cost relative value function for this problem. In addition, the $K$-convexity of discounted relative value functions and their convergence to average-cost relative value functions, when the discount factor increases to 1, imply the $K$-convexity of average-cost relative value functions. This implies that average-cost optimal $(s,S)$ policies for the inventory control problem can be derived from the average-cost optimality equation.

math.OC↗

arXiv2016

A Hierarchical Distributed Processing Framework for Big Image Data

This paper introduces an effective processing framework nominated ICP (Image Cloud Processing) to powerfully cope with the data explosion in image processing field. While most previous researches focus on optimizing the image processing algorithms to gain higher efficiency, our work dedicates to providing a general framework for those image processing algorithms, which can be implemented in parallel so as to achieve a boost in time efficiency without compromising the results performance along with the increasing image scale. The proposed ICP framework consists of two mechanisms, i.e. SICP (Static ICP) and DICP (Dynamic ICP). Specifically, SICP is aimed at processing the big image data pre-stored in the distributed system, while DICP is proposed for dynamic input. To accomplish SICP, two novel data representations named P-Image and Big-Image are designed to cooperate with MapReduce to achieve more optimized configuration and higher efficiency. DICP is implemented through a parallel processing procedure working with the traditional processing mechanism of the distributed system. Representative results of comprehensive experiments on the challenging ImageNet dataset are selected to validate the capacity of our proposed ICP framework over the traditional state-of-the-art methods, both in time efficiency and quality of results.

cs.CV↗

arXiv2015

Generation of three-dimensional entanglement between two spatially separated atoms via shortcuts to adiabatic passage

We propose a scheme for generating three-dimensional entanglement between two atoms trapped in two spatially separated cavities reapectively via shortcuts to adi- abatic passage based on the approach of Lewis-Riesenfeld invariants in cavity quan- tum electronic dynamics. By combining Lewis-Riesenfeld invariants with quantum Zeno dynamics, we can generate three dimensional entanglement of the two atoms with high fidelity. The Numerical simulation results show that the scheme is ro- bust against the decoherences caused by the photon leakage and atomic spontaneous emission.

quant-ph↗

arXiv2015

Deterministic SWAP gate using shortcuts to adiabatic passage

We theoretically propose an alternative method to realize a deterministic SWAP gate using shortcuts to adiabatic passage based on the approach of Lewis- Riesenfeld invariants in cavity quantum electronic dynamics (QED). By combining Lewis-Riesenfeld invariants with quantum Zeno dynamics, the SWAP gate can be achieved deterministically. The strict numerical results show that our scheme is a fast and robust approach to achieve SWAP gate.

quant-ph↗

arXiv2014

A nonlinear tracking algorithm with range-rate measurements based on unbiased measurement conversion

The three-dimensional CMKF-U with only position measurements is extended to solve the nonlinear tracking problem with range-rate measurements in this paper. A pseudo measurement is constructed by the product of range and range-rate measurements to reduce the high nonlinearity of the range-rate measurements with respect to the target state; then the mean and covariance of the converted measurement errors are derived by the measurement conditioned method, showing better consistency than the transitional nested conditioning method; finally, the sequential filter was used to process the converted position and range-rate measurements sequentially to reduce the approximation error in the second-order EKF. Monte Carlo simulations show that the performance of the new tracking algorithm is better than the traditional one based on CMKF-D.

eess.SY↗

arXiv2014

Shortcuts to adiabatic passage for multiqubit controlled phase gate

We propose an alternative scheme of shortcuts to quantum phase gate in a much shorter time based on the approach of Lewis-Riesenfeld invariants in cavity quantum electronic dynamics (QED) systems. This scheme can be used to perform one-qubit phase gate, two-qubit controlled phase gate and also multiqubit controlled phase gate. The strict numerical simulation for some quantum gates are given, and demonstrate that the total operation time of our scheme is shorter than previous schemes and very robustness against decoherence.

quant-ph↗

arXiv2014

Adiabatic passage for three-dimensional entanglement generation through quantum Zeno dynamics

We propose an adiabatic passage approach to generate two atoms three- dimensional entanglement with the help of quantum Zeno dynamics in a time- dependent interacting field. The atoms are trapped in two spatially separated cavi- ties connected by a fiber, so that the individual addressing is needless. Because the scheme is based on the resonant interaction, the time required to generate entangle- ment is greatly shortened. Since the fields remain in vacuum state and all the atoms are in the ground states, the losses due to the excitation of photons and the spon- taneous transition of atoms are suppressed efficiently compared with the dispersive protocols. Numerical simulation results show that the scheme is robust against the decoherences caused by the cavity decay and atomic spontaneous emission. Addi- tionally, the scheme can be generalized to generate N-atom three-dimensional en- tanglement and high-dimensional entanglement for two spatially separated atoms.

quant-ph↗

arXiv2010

Dynamic Resource Coordination and Interference Management for Femtocell Networks

Femtocell is emerging as a key technology to secure the coverage and capacity in indoor environments. However the deployment of a new femtocell layer may originate undesired interference to the whole system. This paper investigates spectrum resource coordination and interference management for the femtocell networks. A resource coordination scheme based on broadcasting resource coordination request messages by the femto mobile is proposed to reduce the system interference.

cs.IT↗