Upper and lower bounds ≈ Upper and lower bounds
View article: Fast Kd-Trees for the Kullback-Leibler Divergence and Other Decomposable Bregman Divergences
Fast Kd-Trees for the Kullback-Leibler Divergence and Other Decomposable Bregman Divergences Open
The contributions of the paper span theoretical and implementational results. First, we prove that Kd-trees can be extended to ℝ^d with the distance measured by an arbitrary Bregman divergence. Perhaps surprisingly, this shows that the tri…
View article
Equivalence Tests Open
Scientists should be able to provide support for the absence of a meaningful effect. Currently, researchers often incorrectly conclude an effect is absent based a nonsignificant result. A widely recommended approach within a frequentist fr…
View article
Asymmetric Metasurfaces with High- Resonances Governed by Bound States in the Continuum Open
We reveal that metasurfaces created by seemingly different lattices of (dielectric or metallic) meta-atoms with broken in-plane symmetry can support sharp high-Q resonances arising from a distortion of symmetry-protected bound states in th…
View article
Majorana bound state in a coupled quantum-dot hybrid-nanowire system Open
Watching Majorana bound states form Majorana bound states (MBSs) are peculiar quasiparticles that may one day become the cornerstone of topological quantum computing. To engineer these states, physicists have used semiconductor nanowires i…
View article
Theoretically Principled Trade-off between Robustness and Accuracy Open
We identify a trade-off between robustness and accuracy that serves as a guiding principle in the design of defenses against adversarial examples. Although this problem has been widely studied empirically, much remains unknown concerning t…
View article
Large Intelligent Surface-Assisted Wireless Communication Exploiting Statistical CSI Open
Large intelligent surface (LIS)-assisted wireless communications have drawn attention worldwide. With the use of low-cost LIS on building walls, signals can be reflected by the LIS and sent out along desired directions by controlling its p…
View article
The Hidden Vulnerability of Distributed Learning in Byzantium Open
While machine learning is going through an era of celebrated success, concerns have been raised about the vulnerability of its backbone: stochastic gradient descent (SGD). Recent approaches have been proposed to ensure the robustness of di…
View article
Security Control for Discrete-Time Stochastic Nonlinear Systems Subject to Deception Attacks Open
This paper is concerned with the security control problem with quadratic cost criterion for a class of discrete-time stochastic nonlinear systems subject to deception attacks. A definition of security in probability is adopted to account f…
View article
Upper limits on the isotropic gravitational-wave background from Advanced LIGO and Advanced Virgo’s third observing run Open
We report results of a search for an isotropic gravitational-wave background (GWB) using data from Advanced LIGO's and Advanced Virgo's third observing run (O3) combined with upper limits from the earlier O1 and O2 runs. Unlike in previous…
View article
TernGrad: ternary gradients to reduce communication in distributed deep learning Open
High network communication cost for synchronizing gradients and parameters is the well-known bottleneck of distributed training. In this work, we propose TernGrad that uses ternary gradients to accelerate distributed deep learning in data …
View article
Performance Evaluation of Non-Orthogonal Multiple Access in Visible Light Communication Open
In this paper, the performance of non-orthogonal multiple access (NOMA) is characterized in a downlink visible light communication system for two separate cases. In the case of guaranteed quality of service (QoS) provisioning, we derive an…
View article
Coarrays, MUSIC, and the Cramér–Rao Bound Open
Sparse linear arrays, such as co-prime arrays and nested arrays, have the\nattractive capability of providing enhanced degrees of freedom. By exploiting\nthe coarray structure, an augmented sample covariance matrix can be constructed\nand …
View article
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models Open
Recent work has shown that it is possible to train deep neural networks that are provably robust to norm-bounded adversarial perturbations. Most of these methods are based on minimizing an upper bound on the worst-case loss over all possib…
View article
Breaking temporal symmetries for emission and absorption Open
Significance Antennas, from radiofrequencies to optics, are forced to transmit and receive with the same efficiency to/from the same direction. The same constraint applies to thermophotovoltaic systems, which are forced to emit as well as …
View article
$f$ -Divergence Inequalities Open
This paper develops systematic approaches to obtain $f$-divergence inequalities, dealing with pairs of probability measures defined on arbitrary alphabets. Functional domination is one such approach, where special emphasis is placed on fin…
View article
Multi-Armed Bandit-Based Client Scheduling for Federated Learning Open
By exploiting the computing power and local data of distributed clients,\nfederated learning (FL) features ubiquitous properties such as reduction of\ncommunication overhead and preserving data privacy. In each communication round\nof FL, …
View article
Sum-Rate Maximization for IRS-Assisted UAV OFDMA Communication Systems Open
IEEE In this paper, we consider the application of intelligent reflecting surface (IRS) in unmanned aerial vehicle (UAV)-based orthogonal frequency division multiple access (OFDMA) communication systems, which exploits both the significant…
View article
A Refined Laser Method and Faster Matrix Multiplication Open
The complexity of matrix multiplication is measured in terms of ω, the smallest real number such that two n × n matrices can be multiplied using O(nω+∊) field operations for all ∊ > 0; the best bound until now is ω < 2.37287 [Le Gall'14]. …
View article
Automatic Targetless Extrinsic Calibration of a 3D Lidar and Camera by Maximizing Mutual Information Open
This paper reports on a mutual information (MI) based algorithm for automatic extrinsic calibration of a 3D laser scanner and optical camera system. By using MI as the registration criterion, our method is able to work in situ without the …
View article
Enhancing the settling time estimation of a class of fixed‐time stable systems Open
Summary In this paper, we provide a new nonconservative upper bound for the settling time of a class of fixed‐time stable systems. To expose the value and the applicability of this result, we present four main contributions. First, we revi…
View article
Distributed Statistical Machine Learning in Adversarial Settings Open
We consider the distributed statistical learning problem over decentralized systems that are prone to adversarial attacks. This setup arises in many practical applications, including Google's Federated Learning. Formally, we focus on a dec…
View article
Localization Requirements for Autonomous Vehicles Open
Autonomous vehicles require precise knowledge of their position and orientation in all weather and traffic conditions for path planning, perception, control, and general safe operation. Here we derive these requirements for autonomous vehi…
View article
Proof of the finite-time thermodynamic uncertainty relation for steady-state currents Open
The thermodynamic uncertainty relation offers a universal energetic constraint on the relative magnitude of current fluctuations in nonequilibrium steady states. However, it has only been derived for long observation times. Here, we prove …
View article
Universal bounds on current fluctuations Open
For current fluctuations in nonequilibrium steady states of Markovian processes, we derive four different universal bounds valid beyond the Gaussian regime. Different variants of these bounds apply to either the entropy change or any indiv…
View article
Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs Open
Given a stream of heterogeneous graphs containing different types of nodes and edges, how can we spot anomalous ones in real-time while consuming bounded memory? This problem is motivated by and generalizes from its application in security…
View article
Maximum Bound Principles for a Class of Semilinear Parabolic Equations and Exponential Time-Differencing Schemes Open
The ubiquity of semilinear parabolic equations has been highlighted in their numerous applications ranging from physics, biology, to materials and social sciences. Here, we consider a practically desirable property for a class of semilinea…
View article
Hybrid Consensus: Efficient Consensus in the Permissionless Model Open
Consensus, or state machine replication is a foundational building block of distributed systems and modern cryptography. Consensus in the classical, "permissioned" setting has been extensively studied in the 30 years of distributed systems…
View article
Two-terminal charge tunneling: Disentangling Majorana zero modes from partially separated Andreev bound states in semiconductor-superconductor heterostructures Open
We demonstrate that partially overlapping Majorana bound states (MBSs) represent a generic low-energy feature that emerges in non-homogeneous semiconductor nanowires coupled to superconductors in the presence of a Zeeman field. The emergen…
View article
Reachability Analysis of Deep Neural Networks with Provable Guarantees Open
Verifying correctness for deep neural networks (DNNs) is challenging. We study a generic reachability problem for feed-forward DNNs which, for a given set of inputs to the network and a Lipschitz-continuous function over its outputs comput…
View article
Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks Open
Despite existing work on ensuring generalization of neural networks in terms of scale sensitive complexity measures, such as norms, margin and sharpness, these complexity measures do not offer an explanation of why neural networks generali…