arXiv subjects

Bo Liu

Publications and source records attributed to Bo Liu.

At least 631 records · Page 35Linked to original sources

arXiv2018

Constrained-size Tensorflow Models for YouTube-8M Video Understanding Challenge

This paper presents our 7th place solution to the second YouTube-8M video understanding competition which challenges participates to build a constrained-size model to classify millions of YouTube videos into thousands of classes. Our final model consists of four single models aggregated into one tensorflow graph. For each single model, we use the same network architecture as in the winning solution of the first YouTube-8M video understanding competition, namely Gated NetVLAD. We train the single models separately in tensorflow's default float32 precision, then replace weights with float16 precision and ensemble them in the evaluation and inference stages., achieving 48.5% compression rate without loss of precision. Our best model achieved 88.324% GAP on private leaderboard. The code is publicly available at https://github.com/boliu61/youtube-8m

cs.CV↗

arXiv2018

QUOTA: The Quantile Option Architecture for Reinforcement Learning

In this paper, we propose the Quantile Option Architecture (QUOTA) for exploration based on recent advances in distributional reinforcement learning (RL). In QUOTA, decision making is based on quantiles of a value distribution, not only the mean. QUOTA provides a new dimension for exploration via making use of both optimism and pessimism of a value distribution. We demonstrate the performance advantage of QUOTA in both challenging video games and physical robot simulators.

cs.LG↗

arXiv2018

Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application to Reinforcement Learning

Dantzig Selector (DS) is widely used in compressed sensing and sparse learning for feature selection and sparse signal recovery. Since the DS formulation is essentially a linear programming optimization, many existing linear programming solvers can be simply applied for scaling up. The DS formulation can be explained as a basis pursuit denoising problem, wherein the data matrix (or measurement matrix) is employed as the denoising matrix to eliminate the observation noise. However, we notice that the data matrix may not be the optimal denoising matrix, as shown by a simple counter-example. This motivates us to pursue a better denoising matrix for defining a general DS formulation. We first define the optimal denoising matrix through a minimax optimization, which turns out to be an NPhard problem. To make the problem computationally tractable, we propose a novel algorithm, termed as Optimal Denoising Dantzig Selector (ODDS), to approximately estimate the optimal denoising matrix. Empirical experiments validate the proposed method. Finally, a novel sparse reinforcement learning algorithm is formulated by extending the proposed ODDS algorithm to temporal difference learning, and empirical experimental results demonstrate to outperform the conventional vanilla DS-TD algorithm.

cs.LG↗

arXiv2018

A Block Coordinate Ascent Algorithm for Mean-Variance Optimization

Risk management in dynamic decision problems is a primary concern in many fields, including financial investment, autonomous driving, and healthcare. The mean-variance function is one of the most widely used objective functions in risk management due to its simplicity and interpretability. Existing algorithms for mean-variance optimization are based on multi-time-scale stochastic approximation, whose learning rate schedules are often hard to tune, and have only asymptotic convergence proof. In this paper, we develop a model-free policy search framework for mean-variance optimization with finite-sample error bound analysis (to local optima). Our starting point is a reformulation of the original mean-variance function with its Fenchel dual, from which we propose a stochastic block coordinate ascent policy search algorithm. Both the asymptotic convergence guarantee of the last iteration's solution and the convergence rate of the randomly picked solution are provided, and their applicability is demonstrated on several benchmark domains.

cs.LG↗

arXiv2018

Parameter Synthesis Problems for Parametric Timed Automata

We consider the parameter synthesis problem of parametric timed automata (PTAs). The problem is, given a PTA and a property, to compute the set of valuations of the parameters under which the resulting timed automaton satisfies the property. Such a set of parameter valuations is called a feasible region for the PTA and the property. The problem is known undecidable in general. This paper, however, presents our study on some decidable sub-classes of PTAs and proposes efficient parameter synthesis algorithms for them.

eess.SY↗

arXiv2018

Novel nonlinear electrodynamics black hole and related phenomena in the extended thermodynamics

In this paper, we present the analytic solution for Anti-de Sitter-Nonlinear electrodynamics (AdS-NED) black hole in four dimensions. We study tunneling of vector particles from the AdS-NED black hole to find Hawking temperature as well as its thermodynamical properties in usual and extended phase space. Then we explore the properties of pressure-volume criticality by analyzing the phase diagram and its free energy. Finally, we investigate the Joule-Thomson coefficient, in which the inversion curve of warming and cooling are studied, and the ratio between the inverse temperature and critical temperature are computed in the black hole solution.

gr-qc↗

arXiv2018

Tricritical point and solid/liquid/gas phase transition of higher dimensional AdS black hole in massive gravity

By considering the fifth order term of the interaction potential in massive gravity theory, we study the $P-V$ critical behaviors of AdS black hole in $d \geq 7$ dimensional space-time, and find the tricritical point and the solid/liquid/gas phase transition in addition to the Van der Waals-like phase and the reentrant phase transition of the system. The critical phenomena of black holes depend crucially on the number $n$ of interaction potential terms.

hep-th↗

arXiv2018

Cosmic Bell Test using Random Measurement Settings from High-Redshift Quasars

In this Letter, we present a cosmic Bell experiment with polarization-entangled photons, in which measurement settings were determined based on real-time measurements of the wavelength of photons from high-redshift quasars, whose light was emitted billions of years ago, the experiment simultaneously ensures locality. Assuming fair sampling for all detected photons and that the wavelength of the quasar photons had not been selectively altered or previewed between emission and detection, we observe statistically significant violation of Bell's inequality by $9.3$ standard deviations, corresponding to an estimated $p$ value of $\lesssim 7.4 \times 10^{-21}$. This experiment pushes back to at least $\sim 7.8$ Gyr ago the most recent time by which any local-realist influences could have exploited the "freedom-of-choice" loophole to engineer the observed Bell violation, excluding any such mechanism from $96\%$ of the space-time volume of the past light cone of our experiment, extending from the big bang to today.

quant-ph↗

arXiv2018

Bloch bound state of spin-orbit-coupled fermions in an optical lattice

Understanding fundamentals of few-body physics provides an interesting bottom-up approach for the clarification of many-body properties. The remarkable experimental progress in realizing spin-orbit coupling (SOC) in optical Raman lattices offers a renewed thrust towards discovering novel few-body features induced by the interplay between SOC and optical lattices. Using the Wilson renormalization method to account for high-band effects, we study the low-energy two-body scattering processes of spin-$1/2$ fermions in spin-orbit coupled optical lattices. We demonstrate that, under weak SOC, adding a small lattice potential would destabilize shallow two-body bound states, contrary to conventional wisdom. On the other hand, when lattice is sufficiently deep, two-body bound states are always stabilized by increasing the lattice depth. This intriguing non-monotonic behavior of the bound-state stability derives from the competition between SOC and optical lattices, and can be explained by analyzing the low-energy density of states. We also discuss the impact of high-band effects on such a behavior, as well as potential experimental detections.

cond-mat.quant-gas↗

arXiv2018

Reconstruction of physics objects at the Circular Electron Positron Collider with Arbor

After the Higgs discovery, precise measurements of the Higgs properties and the electroweak observables become vital for the experimental particle physics. A powerful Higgs/Z factory, the Circular Electron Positron Collider(CEPC) is proposed. The Particle Flow oriented detector design is proposed to the CEPC and a Particle Flow algorithm, Arbor is optimized accordingly. We summarize the physics object reconstruction performance of the Particle Flow oriented detector design with Arbor algorithm and conclude that this combination fulfills the physics requirement of CEPC.

hep-ex↗

arXiv2018

PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making

Reinforcement learning and symbolic planning have both been used to build intelligent autonomous agents. Reinforcement learning relies on learning from interactions with real world, which often requires an unfeasibly large amount of experience. Symbolic planning relies on manually crafted symbolic knowledge, which may not be robust to domain uncertainties and changes. In this paper we present a unified framework {\em PEORL} that integrates symbolic planning with hierarchical reinforcement learning (HRL) to cope with decision-making in a dynamic environment with uncertainties. Symbolic plans are used to guide the agent's task execution and learning, and the learned experience is fed back to symbolic knowledge to improve planning. This method leads to rapid policy search and robust symbolic plans in complex domains. The framework is tested on benchmark domains of HRL.

cs.LG↗

arXiv2018

Privacy Preservation in Location-Based Services: A Novel Metric and Attack Model

Recent years have seen rising needs for location-based services in our everyday life. Aside from the many advantages provided by these services, they have caused serious concerns regarding the location privacy of users. An adversary such as an untrusted location-based server can monitor the queried locations by a user to infer critical information such as the user's home address, health conditions, shopping habits, etc. To address this issue, dummy-based algorithms have been developed to increase the anonymity of users, and thus, protecting their privacy. Unfortunately, the existing algorithms only consider a limited amount of side information known by an adversary which may face more serious challenges in practice. In this paper, we incorporate a new type of side information based on consecutive location changes of users and propose a new metric called transition-entropy to investigate the location privacy preservation, followed by two algorithms to improve the transition-entropy for a given dummy generation algorithm. Then, we develop an attack model based on the Viterbi algorithm which can significantly threaten the location privacy of the users. Next, in order to protect the users from Viterbi attack, we propose an algorithm called robust dummy generation (RDG) which can resist against the Viterbi attack while maintaining a high performance in terms of the privacy metrics introduced in the paper. All the algorithms are applied and analyzed on a real-life dataset.

cs.CR↗

arXiv2018

Quantum temporal steering in a dephasing channel with quantum criticality

We investigate the quantum temporal steering (TS), i.e., a temporal analogue of Einstein-Podolsky-Rosen steering, in a dephasing channel which is modeled by a central spin half surrounded by a spin-1/2 \textit{XY} chain where quantum phase transition happens. The TS parameter $S_{\text{TS}}$ and the TS weight $W_{\text{TS}}$ are employed to characterize the TS dynamics. We analytically obtain the dependence of $S_{\text{TS}}$ on the decoherence factor. The numerical results show an obvious suppression of $S_{\text{TS}}$ and $W_{\text{TS}}$ when the \textit{XY} chain approaches to the critical point. In view of the significance of quantum channel, we develop a new concept, \textit{TS weight power}, in order to quantify the capacity of the quantum channel in dominating TS behavior. This new quantity enables us to indicate the quantum criticality of the environment by the quantum correlation of TS in the coupled system.

quant-ph↗

arXiv2018

Graphene Nanoribbon as an Elastic Damper

Heterostructures composed of dissimilar two-dimensional nanomaterials can have nontrivial physical and mechanical properties promising for many applications. Interestingly, in some cases, it is possible to create heterostructures composed of weakly and strongly stretched domains with the same chemical composition, as it has been demonstrated for some polymer chains, DNA, and intermetallic nanowires supporting this effect of two-phase stretching. These materials at relatively strong tension forces split into domains with smaller and larger tensile strain. Within this region, average strain increases at constant tensile force due to the growth of the domain with the larger strain in the expense of the domain with smaller strain. Here the two-phase stretching phenomenon is described for graphene nanoribbons with the help of molecular dynamics simulations. This unprecedented feature of graphene revealed in our study is related to the peculiarities of nucleation and motion of the domain walls separating the domains with different elastic strain. It turns out that the loading-unloading curves exhibit a hysteresis-like behavior due to the energy dissipation during the domain wall nucleation and motion. Here, we originally put forward the idea of implementing graphene nanoribbons as elastic dampers, efficiently converting mechanical strain energy into heat during cyclic loading-unloading through elastic extension where domains with larger and smaller strain coexist. Furthermore, in the regime of two-phase stretching, graphene nanoribbon is a heterostructure for which the fraction of domains with larger and smaller strain, and consequently its physical and mechanical properties, can be tuned in a controllable manner by applying elastic strain and/or heat.

cond-mat.mtrl-sci↗

arXiv2018

Real embedding and equivariant eta forms

In 1993, Bismut and Zhang establish a mod Z embedding formula of Atiyah-Patodi-Singer reduced eta invariants. In this paper, we explain the hidden mod Z term as a spectral flow and extend this embedding formula to the equivariant family case. In this case, the spectral flow is generalized to the equivariant chern character of some equivariant Dai-Zhang higher spectral flow.

math.DG↗

arXiv2018

Emergent interlayer nodal superfluidity of a dipolar fermi gas in bilayer optical lattices

Understanding the interplay between magnetism and superconductivity is one of the central issues in condensed matter physics. Such interplay induced nodal structure of superconducting gap is widely believed to be a signature of exotic pairing mechanism (not phonon mediated) to achieve unconventional superconductivity, such as in heavy fermion, high $T_c$, and organic superconductors. Here we report a new mechanism to drive the interplay between magnetism and superfluidity via the spatially anisotropic interaction. This scheme frees up the usual requirement of suppressing long-range magnetic order to access unconventional superconductivity like through doping or adding pressure in solids. Surprisingly, even for the half-filling case, such scheme can lead the coexistence of superfluidity and antiferromagnetism and interestingly an unexpected interlayer nodal superfluid emerges, which will be demonstrated through a cold atom system composed of a pseudospin-$1/2$ dipolar fermi gas in bilayer optical lattices. Our mechanism should pave an alternative way to unveil exotic pairing scheme resulting from the interplay between magnetism and superconductivity or superfluidity.

cond-mat.quant-gas↗

arXiv2018

Satellite-relayed intercontinental quantum network

We perform decoy-state quantum key distribution between a low-Earth-orbit satellite and multiple ground stations located in Xinglong, Nanshan, and Graz, which establish satellite-to-ground secure keys with ~kHz rate per passage of the satellite Micius over a ground station. The satellite thus establishes a secure key between itself and, say, Xinglong, and another key between itself and, say, Graz. Then, upon request from the ground command, Micius acts as a trusted relay. It performs bitwise exclusive OR operations between the two keys and relays the result to one of the ground stations. That way, a secret key is created between China and Europe at locations separated by 7600 km on Earth. These keys are then used for intercontinental quantum-secured communication. This was on the one hand the transmission of images in a one-time pad configuration from China to Austria as well as from Austria to China. Also, a videoconference was performed between the Austrian Academy of Sciences and the Chinese Academy of Sciences, which also included a 280 km optical ground connection between Xinglong and Beijing. Our work points towards an efficient solution for an ultralong-distance global quantum network, laying the groundwork for a future quantum internet.

quant-ph↗

arXiv2017

Searching for the Transit of the Earth--mass exoplanet Proxima~Centauri~b in Antarctica: Preliminary Result

Proxima Centauri is known as the closest star from the Sun. Recently, radial velocity observations revealed the existence of an Earth-mass planet around it. With an orbital period of ~11 days, the surface of Proxima Centauri b is temperate and might be habitable. We took a photometric monitoring campaign to search for its transit, using the Bright Star Survey Telescope at the Zhongshan Station in Antarctica. A transit-like signal appearing on 2016 September 8th, is identified tentatively. Its midtime, $T_{C}=2,457,640.1990\pm0.0017$ HJD, is consistent with the predicted ephemeris based on RV orbit in a 1$σ$ confidence interval. Time-correlated noise is pronounced in the light curve of Proxima Centauri, affecting detection of transits. We develop a technique, in a Gaussian process framework, to gauge the statistical significance of potential transit detection. The tentative transit signal reported here, has a confidence level of $2.5σ$. Further detection of its periodic signals is necessary to confirm the planetary transit of Proxima Centauri b. We plan to monitor Proxima Centauri in next Polar night at Dome A in Antarctica, taking the advantage of continuous darkness. \citet{Kipping17} reported two tentative transit-like signals of Proxima Centauri b, observed by the Microvariability and Oscillation of Stars space Telescope in 2014 and 2015, respectively. The midtransit time of our detection is 138 minutes later than that predicted by their transit ephemeris. If all the signals are real transits, the misalignment of the epochs plausibly suggests transit timing variations of Proxima Centauri b induced by an outer planet in this system.

astro-ph.EP↗