November 2022 arXiv papers — page 15

S. Phillipps, S. Bellstedt, M. N. Bremer, R. De Propris

The star formation rate in galaxies is well known to correlate with stellar mass (the `star-forming main sequence'). Here we extend this further to explore any additional dependence on galaxy surface brightness, a proxy for stellar mass surface density. We use a large sample of low redshift ($z \leq 0.08$) galaxies from the GAMA survey which have both SED de

Karli Gillette, Matthias A. F. Gsell, Claudia Nagel, Jule Bender

Mechanistic cardiac electrophysiology models allow for personalized simulations of the electrical activity in the heart and the ensuing electrocardiogram (ECG) on the body surface. As such, synthetic signals possess known ground truth labels of the underlying disease and can be employed for validation of machine learning ECG analysis tools in addition to cli

Willian Corrêa

M. Daher [9] showed that if $(X_0, X_1)$ is a regular couple of uniformly convex spaces then the unit spheres of the complex interpolation spaces $X_{\theta}$ and $X_{\eta}$ are uniformly homeomorphic for every $0 < \theta, \eta < 1$. We show that this is a rather general phenomenon of interpolation methods described by the discrete framework of interpolatio

Xiaochuan Ni, Xiaoling Zhang, Xu Zhan, Zhenyu Yang

This work focuses on multi-target tracking in Video synthetic aperture radar. Specifically, we refer to tracking based on targets' shadows. Current methods have limited accuracy as they fail to consider shadows' characteristics and surroundings fully. Shades are low-scattering and varied, resulting in missed tracking. Surroundings can cause interferences, re

M Muhsin, M Sahoo

We consider an inertial active Ornstein-Uhlenbeck particle self-propelling in a saw-tooth ratchet potential. Using the Langevin simulation and matrix continued fraction method, the particle transport, steady state diffusion, and coherence in transport are investigated throughout the ratchet. Spatial asymmetry is found to be the key criterion for the possibil

Qin Wang, Guangsheng Yu, Yilin Sai, Caijun Sun

Decentralized Autonomous Organization (DAO) is an organization constructed by automatically executed rules such as via smart contracts, holding features of the permissionless committee, transparent proposals, and fair contribution by stakeholders. As of Nov 2022, DAO has impacted over \$11.2B market caps. However, there are no substantial studies focused on

Eun Sun Lee, Junho Kim, SangWon Park, Young Min Kim

We propose a domain adaptation method, MoDA, which adapts a pretrained embodied agent to a new, noisy environment without ground-truth supervision. Map-based memory provides important contextual information for visual navigation, and exhibits unique spatial structure mainly composed of flat walls and rectangular obstacles. Our adaptation approach encourages

Dimitrios Betsakos, Alexander Yu. Solynin

We consider solutions $u_f$ to the one-dimensional Robin problem with the heat source $f\in L^1[-\pi,\pi]$ and Robin parameter $\alpha>0$. For given $m$, $M$, and $s$, $0\le m<s<M$, we identify the heat sources $f_0$, such that $u_{f_0}$ maximizes the temperature gap $\max_{[-\pi,\pi]}u_f -\min_{[-\pi,\pi]}u_f$ over all heat sources $f$ such that $m\le f\le

Lyutianyang Zhang, Sumit Roy

Beam training of 802.11 ad is a technology that helps accelerate the analog weighting vector (AWV) selection process under the constraint of the existing code-book for AWV. However, 5G milli-meter wave (mmWave) multiple-input-multiple-output (MIMO) system brings challenges to this new technology due to the higher order of complexity of antennae. Hence, the e

R. M. Green

Let $S_k \times S_{n-k}$ be a maximal Young subgroup of the symmetric group $S_n$. We introduce a basis ${\mathcal B}_{n,k}$ for the coset space $S_n/S_k \times S_{n-k}$ that is naturally parametrized by the set of standard Young tableaux with $n$ boxes, at most two rows, and at most $k$ boxes in the second row. The basis ${\mathcal B}_{n,k}$ has positivity

Gabriele Etta, Emanuele Sangiorgio, Niccolò Di Marco, Michele Avalle

Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collect

Bowen Yu, Zhenyu Zhang, Jingyang Li, Haiyang Yu

Open Information Extraction (OpenIE) facilitates the open-domain discovery of textual facts. However, the prevailing solutions evaluate OpenIE models on in-domain test sets aside from the training corpus, which certainly violates the initial task principle of domain-independence. In this paper, we propose to advance OpenIE towards a more realistic scenario:

Minjin Choi, Eunok Bae, Soojoon Lee

Quantifying entanglement is vital to understand entanglement as a resource in quantum information processing, and many entanglement measures have been suggested for this purpose. When mathematically defining an entanglement measure, we should consider the distinguishability between entangled and separable states, the invariance under local transformation, th

Jorgen S Frederiksen

Dynamical vectors characterizing instability and applicable as ensemble perturbations for prediction with geophysical fluid dynamical models are analysed. The relationships between covariant Lyapunov vectors (CLVs), orthonormal Lyapunov vectors (OLVs), singular vectors (SVs), Floquet vectors and finite-time normal modes (FTNMs) are examined for periodic and

Aleksei S. Komlev, Rodion A. Makarin, Tatiana S. Ilina, Dmitry A. Kiselev

The FeRh alloy is an attractive material for studies of magnetic first-order phase transitions. The phase transition in FeRh from an antiferromagnetic to the ferromagnetic state is accompanied by the nucleation, growth, and merging of ferromagnetic clusters. The ferromagnetic phase evolution is studied in detail, and its various stages are distinguished. Bot

Shahar Hod

It is proved that spherically symmetric extermal black holes possess at least one external light ring. Our remarkably compact proof is based on the dominant energy condition which characterizes the external matter fields in the non-vacuum extremal black-hole spacetimes.

Li Yang, Jiang Hu, Zhidong Bai

Let $G$ be a finite Abelian group of order $d$. We consider an urn in which, initially, there are labeled balls that generate the group $G$. Choosing two balls from the urn with replacement, observe their labels, and perform a group multiplication on the respective group elements to obtain a group element. Then, we put a ball labeled with that resulting elem

Moritz Hiebler, Sarah Nakato, Roswitha Rissner

Rings of integer-valued polynomials are known to be atomic, non-factorial rings furnishing examples for both irreducible elements for which all powers factor uniquely (\emph{absolutely irreducibles}) and irreducible elements where some power has a factorization different from the trivial one. In this paper, we study irreducible polynomials $F \in \operatorna

Shengjie Li, Vincent Ng

We adapt Lee et al.'s (2018) span-based entity coreference model to the task of end-to-end discourse deixis resolution in dialogue, specifically by proposing extensions to their model that exploit task-specific characteristics. The resulting model, dd-utt, achieves state-of-the-art results on the four datasets in the CODI-CRAC 2021 shared task.

Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang

Air pollution is a crucial issue affecting human health and livelihoods, as well as one of the barriers to economic and social growth. Forecasting air quality has become an increasingly important endeavor with significant social impacts, especially in emerging countries like China. In this paper, we present a novel Transformer architecture termed AirFormer t

Atithi Acharya, Manuel Rudolph, Jing Chen, Jacob Miller

With the advent of quantum and quantum-inspired machine learning, adapting the structure of learning models to match the structure of target datasets has been shown to be crucial for obtaining high performance. Probabilistic models based on tensor networks (TNs) are prime candidates to benefit from data-dependent design considerations, owing to their bias to

Shuangkang Fang, Weixin Xu, Heng Wang, Yi Yang

Neural Radiance Fields (NeRF) methods have proved effective as compact, high-quality and versatile representations for 3D scenes, and enable downstream tasks such as editing, retrieval, navigation, etc. Various neural architectures are vying for the core structure of NeRF, including the plain Multi-Layer Perceptron (MLP), sparse tensors, low-rank tensors, ha

Kaiyuan Cao, Shuxiang Yang, Yayun Hu, Guangwen Yang

The dynamics of the geometric phase are studied in inhomogeneous quantum spin chains after a quench. Analytic expressions of the Pancharatnam geometric phase (PGP) $\mathcal{G}(t)$ are derived, for both the period-two quantum Ising chain (QIC) and the disordered QIC. In the period-two QIC, due to the periodic modulation, the PGP changes with time at the boun

Xinyu Cai, Wentao Jiang, Runsheng Xu, Wenquan Zhao

Recently, Vehicle-to-Everything(V2X) cooperative perception has attracted increasing attention. Infrastructure sensors play a critical role in this research field; however, how to find the optimal placement of infrastructure sensors is rarely studied. In this paper, we investigate the problem of infrastructure sensor placement and propose a pipeline that can

Yang Ai, Zhen-Hua Ling

This paper presents a novel speech phase prediction model which predicts wrapped phase spectra directly from amplitude spectra by neural networks. The proposed model is a cascade of a residual convolutional network and a parallel estimation architecture. The parallel estimation architecture is composed of two parallel linear convolutional layers and a phase

Ruicheng Bao, Zhonghuai Hou

Entropy production plays an important role in the regulation and stability of active matter systems, and its rate quantifies the nonequilibrium nature of these systems. However, entropy production is hard to be experimentally estimated even in some simple active systems like molecular motors or bacteria, which may be modeled by the run-and-tumble particle (R

Shiyang Sun, Xuyan Chen, Xuqi Li, Huihui Zhang

The exploration of magnetism in two-dimensional layered materials has attracted extensive research interest. For the monoclinic phase CrI3 with interlayer antiferromagnetism, finding a static and robust way of realizing the intrinsic interlayer ferromagnetic coupling is desirable. In this Letter, we study the electronic structure and magnetic properties of t

Ian Stewart, Katherine Keith

Many scientific fields -- including biology, health, education, and the social sciences -- use machine learning (ML) to help them analyze data at an unprecedented scale. However, ML researchers who develop advanced methods rarely provide detailed tutorials showing how to apply these methods. Existing tutorials are often costly to participants, presume extens

Michael Entov, Misha Verbitsky

Consider a symplectic embedding of a disjoint union of domains into a symplectic manifold $M$. Such an embedding is called Kahler-type, or respectively tame, if it is holomorphic with respect to some (not a priori fixed, Kahler-type) complex structure on $M$ compatible with the symplectic form, or respectively tamed by it. Assume that $M$ either of the follo

Yabin Wang, Zhiheng Ma, Zhiwu Huang, Yaowei Wang

This paper focuses on the prevalent performance imbalance in the stages of incremental learning. To avoid obvious stage learning bottlenecks, we propose a brand-new stage-isolation based incremental learning framework, which leverages a series of stage-isolated classifiers to perform the learning task of each stage without the interference of others. To be c

Andrew Suk, Ji Zeng

A finite point set in $\mathbb{R}^d$ is in general position if no $d + 1$ points lie on a common hyperplane. Let $\alpha_d(N)$ be the largest integer such that any set of $N$ points in $\mathbb{R}^d$, with no $d + 2$ members on a common hyperplane, contains a subset of size $\alpha_d(N)$ in general position. Using the method of hypergraph containers, Balogh

Yu-Cheng Qiu, Tsutomu T. Yanagida

The electroweak axion is identified with the fuzzy dark matter of a mass $m\simeq 10^{-20}$--$10^{-19}\,{\rm eV}$. The model predicts two components of dark matter, one is ultralight and the other is WIMP-like. The Chern-Simons-type interaction between the fuzzy dark matter and photon and the $B+L$ breaking proton decays are predicted.

Tao Wang, Shan-Qin Wang, Wen-Pei Gan, Long Li

In this paper, we perform a comprehensive study for the physical properties of SN 2018gk which is a luminous type IIb supernova (SN). We find that the early-time photospheric velocity vary from a larger value to a smaller value before the photosphere reach a temperature floor. We generalize the photosphere modulus and fit the multi-band light curves (LCs) of

Kenji Imamura, Eiichiro Sumita

Multilingual pretrained models are effective for machine translation and cross-lingual processing because they contain multiple languages in one model. However, they are pretrained after their tokenizers are fixed; therefore it is difficult to change the vocabulary after pretraining. When we extend the pretrained models to new languages, we must modify the t

B. L. S. Prakasa Rao

We discuss some conditional generalized Borel-Cantelli lemmas and investigate their quantitative versions following the ideas of Arthan and Oliva (arXiv: 2012.09942).

Wenlian Lu, Xin Du, Jiexiang Wang, Longbin Zeng

Here, we present the Digital Brain (DB), a platform for simulating spiking neuronal networks at the large neuron scale of the human brain based on personalized magnetic-resonance-imaging data and biological constraints. The DB aims to reproduce both the resting state and certain aspects of the action of the human brain. An architecture with up to 86 billion

P. M. Lavrov

New method (arXiv:2104.11930) is applied to construct cubic interactions of massless spin 4 and real scalar fields. In contrast with the case of massless spin 3 fields (arXiv:2208.05700, 2209.03678, 2210.02842) the procedure requires to use an unconstrained formulation (arXiv:0702.161) for the Fronsdal theory. It is shown that in the unconstrained formulatio

Yuqing Gao, Pengyuan Zhai, Khalid M. Mosalam

In recent years, applying deep learning (DL) to assess structural damages has gained growing popularity in vision-based structural health monitoring (SHM). However, both data deficiency and class-imbalance hinder the wide adoption of DL in practical applications of SHM. Common mitigation strategies include transfer learning, over-sampling, and under-sampling

Adarsh Ganeshram, Haydn Maust, Valentin Duruisseaux, Zongyi Li

The physics-informed neural operator (PINO) is a machine learning paradigm that has demonstrated promising results for learning solutions to partial differential equations (PDEs). It leverages the Fourier Neural Operator to learn solution operators in function spaces and leverages physics losses during training to penalize deviations from known physics laws.

Xu Zhang, Paul Schmitt, Marshini Chetty, Nick Feamster

The emerging video applications greatly increase the demand in network bandwidth that is not easy to scale. To provide higher quality of experience (QoE) under limited bandwidth, a recent trend is to leverage the heterogeneity of quality preferences across individual users. Although these efforts have suggested the great potential benefits, service providers

Chongyao Chen, Ziang Chen, Jianfeng Lu

In this work, we establish a representation theorem for multivariable totally symmetric functions: a multisymmetric continuous function must be the composition of a continuous function and a set of generators of the multisymmetric polynomials. We then study the singularity and geometry of the generators, and show that the regularity may become worse after ap

Siyu Liu, Marija Ilic

This paper concerns the resilience of systems with wind power upon wind reduction by evaluating the potential of corrective actions, such as generation and load dispatch, on minimizing the effects of transmission line failures. Three functions (grid, consumer-centric loss, and resilience impact) are used to statistically evaluate the criticality of initial c

Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai

Behavior constrained policy optimization has been demonstrated to be a successful paradigm for tackling Offline Reinforcement Learning. By exploiting historical transitions, a policy is trained to maximize a learned value function while constrained by the behavior policy to avoid a significant distributional shift. In this paper, we propose our closed-form p

Chu-Chun Chuang, Chien-Yi Wang, Shang-Hong Lai

With the increasing variations of face presentation attacks, model generalization becomes an essential challenge for a practical face anti-spoofing system. This paper presents a generalized face anti-spoofing framework that consists of three tasks: depth estimation, face parsing, and live/spoof classification. With the pixel-wise supervision from the face pa

Tobias Felkl, Adam Lackner, Michael A. Schmidt

We investigate if the projected high-precision measurements of the cross section of the Higgsstrahlung process $e^+ e^- \to Zh$ at a future electron-positron collider can be utilised to indirectly probe the fermionic Seesaw models. We consider the two centre-of-mass energies $\sqrt{s}=240$ GeV and $365$ GeV, and compare the collider reaches to constraints fr

Fan He, Ruikai Yang, Lei Shi, Xiaolin Huang

This paper studies kernel PCA in a decentralized setting, where data are distributively observed with full features in local nodes and a fusion center is prohibited. Compared with linear PCA, the use of kernel brings challenges to the design of decentralized consensus optimization: the local projection directions are data-dependent. As a result, the consensu

Ching Hung Lam

We prove that all holomorphic vertex operator algebras of central charge $24$ with non-trivial weight one subspaces are unitary. The main method is to use the orbifold construction of a holomorphic VOA $V$ of central charge $24$ directly from a Niemeier lattice VOA $V_N$. We show that it is possible to extend the unitary form for the lattice VOA $V_N$ to the

HyeonCheol Moon, JinWoo Jeong, SungJei Kim

Recently, CNN-based SISR has numerous parameters and high computational cost to achieve better performance, limiting its applicability to resource-constrained devices such as mobile. As one of the methods to make the network efficient, Knowledge Distillation (KD), which transfers teacher's useful knowledge to student, is currently being studied. More recentl

Kyungsu Kim, Chae Yeon Lim, Joong Bo Shin, Myung Jin Chung

The cone-beam computed tomography (CBCT) provides 3D volumetric imaging of a target with low radiation dose and cost compared with conventional computed tomography, and it is widely used in the detection of paranasal sinus disease. However, it lacks the sensitivity to detect soft tissue lesions owing to reconstruction constraints. Consequently, only physicia

Ming-Hsiu Hsieh, Alex Krotz, Roel Tempelaar

Mean-field mixed quantum--classical dynamics could provide a much-needed means to inexpensively model quantum electrodynamical phenomena, by describing the optical field and its vacuum fluctuations classically. However, this approach is known to suffer from an unphysical transfer of energy out of the vacuum fluctuations when the light--matter coupling become

Jaekwon Im, Soonbeom Choi, Sangeon Yong, Juhan Nam

Singing voice separation (SVS) is a task that separates singing voice audio from its mixture with instrumental audio. Previous SVS studies have mainly employed the spectrogram masking method which requires a large dimensionality in predicting the binary masks. In addition, they focused on extracting a vocal stem that retains the wet sound with the reverberat

Oleksandr Tomalak, Kaushik Borah, Richard J. Hill, Kevin S. McFarland

Inverse muon decay ($\nu_\mu e^- \to \nu_e \mu^-$) is a promising tool to constrain neutrino fluxes with energies $E_{\nu} \ge 10.9~\mathrm{GeV}$. Radiative corrections introduce percent-level distortions to energy spectra of outgoing muons and depend on experimental details. In this paper, we calculate radiative corrections to the scattering processes $\nu_

Yvette Kosmann-Schwarzbach

Sim\'eon-Denis Poisson was 25 years old when he was appointed Professor of Mathematics at the \'Ecole Polytechnique in 1806. Elected to the Paris Acad\'emie des Sciences six years later, he soon became one of its most influential members. The origin and later developments of the many concepts in mathematics and physics that bear his name make interesting sto

Ce Jin, Jakob Nogler

Longest Common Substring (LCS) is an important text processing problem, which has recently been investigated in the quantum query model. The decisional version of this problem, LCS with threshold $d$, asks whether two length-$n$ input strings have a common substring of length $d$. The two extreme cases, $d=1$ and $d=n$, correspond respectively to Element Dis

Samuel Kessler, Mateusz Ostaszewski, Michał Bortkiewicz, Mateusz Żarski

World models power some of the most efficient reinforcement learning algorithms. In this work, we showcase that they can be harnessed for continual learning - a situation when the agent faces changing environments. World models typically employ a replay buffer for training, which can be naturally extended to continual learning. We systematically study how di

Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar

We propose a trust-region stochastic sequential quadratic programming algorithm (TR-StoSQP) to solve nonlinear optimization problems with stochastic objectives and deterministic equality constraints. We consider a fully stochastic setting, where at each step a single sample is generated to estimate the objective gradient. The algorithm adaptively selects the

Motohiko Ezawa, Shun Yasunaga, Tetsuya Iizuka, Akio Higo

We propose a universal quantum computer based on a chain of carbon nanotube rotators where one metallic plate is attached to each rotator. The dynamical variable is the rotational angle $\phi$. The attached plate connected to ground electrostatically interacts with two fixed plates. Two angle positions $\phi =0,\pi$ are made stable by applying a voltage diff

Minrui Xu, Xiaoxu Ren, Dusit Niyato, Jiawen Kang

With the drive to create a decentralized digital economy, Web 3.0 has become a cornerstone of digital transformation, developed on the basis of computing-force networking, distributed data storage, and blockchain. With the rapid realization of quantum devices, Web 3.0 is being developed in parallel with the deployment of quantum cloud computing and quantum I

Zhihao Zhang, Siwen Luo, Junyi Chen, Sijia Lai

We propose a PiggyBack, a Visual Question Answering platform that allows users to apply the state-of-the-art visual-language pretrained models easily. The PiggyBack supports the full stack of visual question answering tasks, specifically data processing, model fine-tuning, and result visualisation. We integrate visual-language models, pretrained by HuggingFa

D. Kandel, Roger W. Romani

The optical study of the heated substellar companions of `Black Widow' (BW) millisecond pulsars (MSP) provides unique information on the MSP particle and radiation output and on the neutron star mass. Here we present analysis of optical photometry and spectroscopy of a set of relatively bright BWs, many newly discovered in association with Fermi $\gamma$-ray

Wentao Yu, Yifei Shen, Hengtao He, Xianghao Yu

Terahertz ultra-massive MIMO (THz UM-MIMO) is envisioned as one of the key enablers of 6G wireless networks, for which channel estimation is highly challenging. Traditional analytical estimation methods are no longer effective, as the enlarged array aperture and the small wavelength result in a mixture of far-field and near-field paths, constituting a hybrid

Reza Attarzadeh, Hossein Bagheri, Iman Khosravi, Saeid Niazmardi

Synergetic use of sensors for soil moisture retrieval is attracting considerable interest due to the different advantages of different sensors. Active, passive, and optic data integration could be a comprehensive solution for exploiting the advantages of different sensors aimed at preparing soil moisture maps. Typically, pixel-based methods are used for mult

Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson

Facial analysis systems have been deployed by large companies and critiqued by scholars and activists for the past decade. Many existing algorithmic audits examine the performance of these systems on later stage elements of facial analysis systems like facial recognition and age, emotion, or perceived gender prediction; however, a core component to these sys

Carlos Martin, Tuomas Sandholm

We study the problem of computing an approximate Nash equilibrium of continuous-action game without access to gradients. Such game access is common in reinforcement learning settings, where the environment is typically treated as a black box. To tackle this problem, we apply zeroth-order optimization techniques that combine smoothed gradient estimators with

Samarth Sinha, Jason Y. Zhang, Andrea Tagliasacchi, Igor Gilitschenski

Camera pose estimation is a key step in standard 3D reconstruction pipelines that operate on a dense set of images of a single object or scene. However, methods for pose estimation often fail when only a few images are available because they rely on the ability to robustly identify and match visual features between image pairs. While these methods can work r

Hirokazu Sasaki, Toshihiko Kawano, Ionel Stetcu

We derive the equations of quasiparticle random-phase approximation (QRPA) based on the finite amplitude method (FAM) with the Hartree-Fock+BCS (HF+BCS) single-particle states, and calculate the magnetic dipole (M1) transition for deformed gadolinium isotopes. Our QRPA calculation shows both large spin-flip transitions in the 5 to 10 MeV excitation energy an

Jinghao Sun, Forrest W. Crawford

Many real-world processes are trajectories that may be regarded as continuous-time "functional data". Examples include patients' biomarker concentrations, environmental pollutant levels, and prices of stocks. Corresponding advances in data collection have yielded near continuous-time measurements, from e.g. physiological monitors, wearable digital devices, a

Corentin Ferry, Steven Derrien, Sanjay Rajopadhye

Programs admitting a polyhedral representation can be transformed in many ways for locality and parallelism, notably loop tiling. Data flow analysis can then compute dependence relations between iterations and between tiles. When tiling is applied, certain iteration-wise dependences cross tile boundaries, creating the need for inter-tile data communication.

D. V. Osipov

The Bott-Thurston cocycle is a $2$-cocycle on the group of orientation-preserving diffeomorphisms of the circle. We introduce and study a formal analog of Bott-Thurston cocycle. The formal Bott-Thurston cocycle is a $2$-cocycle on the group of continuous $A$-automorphisms of the algebra $A((t))$ of Laurent series over a commutative ring $A$ with values in th

Wanqiao Xu, Shi Dong, Benjamin Van Roy

We develop an extension of posterior sampling for reinforcement learning (PSRL) that is suited for a continuing agent-environment interface and integrates naturally into agent designs that scale to complex environments. The approach, continuing PSRL, maintains a statistically plausible model of the environment and follows a policy that maximizes expected $\g

Yue Zhao, Jiequn Han

This work is concerned with solving neural network-based feedback controllers efficiently for optimal control problems. We first conduct a comparative study of two prevalent approaches: offline supervised learning and online direct policy optimization. Albeit the training part of the supervised learning approach is relatively easy, the success of the method

Guanhong Tao, Zhenting Wang, Siyuan Cheng, Shiqing Ma

We conduct a systematic study of backdoor vulnerabilities in normally trained Deep Learning models. They are as dangerous as backdoors injected by data poisoning because both can be equally exploited. We leverage 20 different types of injected backdoor attacks in the literature as the guidance and study their correspondences in normally trained models, which

Ekta Patel, Kaisey S. Mandel

We present new mass estimates for Andromeda (M31) using the orbital angular momenta of four satellite galaxies (M33, NGC 185, NGC 147, IC 10) derived from existing proper motions, distances, and line-of-sight velocities. We infer two masses for M31: $M_{\rm vir}= 2.85^{+1.47}_{-0.77}\times10^{12}\, M_{\odot}$ using satellite galaxy phase space information de

Daniel Campos, Daniel Perry, Samir Joshi, Yashmeet Gambhir

Experience management is an emerging business area where organizations focus on understanding the feedback of customers and employees in order to improve their end-to-end experiences. This results in a unique set of machine learning problems to help understand how people feel, discover issues they care about, and find which actions need to be taken on data t

Eldor Abdukhamidov, Mohammed Abuhamad, Simon S. Woo, Eric Chan-Tin

Deep learning methods have gained increased attention in various applications due to their outstanding performance. For exploring how this high performance relates to the proper use of data artifacts and the accurate problem formulation of a given task, interpretation models have become a crucial component in developing deep learning-based systems. Interpret

Osama Yousuf, Imtiaz Hossen, Matthew W. Daniels, Martin Lueker-Boden

Data-driven modeling approaches such as jump tables are promising techniques to model populations of resistive random-access memory (ReRAM) or other emerging memory devices for hardware neural network simulations. As these tables rely on data interpolation, this work explores the open questions about their fidelity in relation to the stochastic device behavi

Jacopo Teneggi, Paul H. Yi, Jeremias Sulam

Modern machine learning pipelines, in particular those based on deep learning (DL) models, require large amounts of labeled data. For classification problems, the most common learning paradigm consists of presenting labeled examples during training, thus providing strong supervision on what constitutes positive and negative samples. This constitutes a major

Alex Devonport, Peter Seiler, Murat Arcak

Complex-valued Gaussian processes are used in Bayesian frequency-domain system identification as prior models for regression. If each realization of such a process were an $H_\infty$ function with probability one, then the same model could be used for probabilistic robust control, allowing for robustly safe learning. We investigate sufficient conditions for

Huarong Zhang, Dongsheng Zhao

The residuated lattices form one of the most important algebras of fuzzy logics and have been heavily studied by people from various different points of view. Sheaf presentations provide a topological approach to many algebraic structures. In this paper, we study the topological properties of prime spectrum of residuated lattices, and then construct a sheaf

Weiyuan Tang, Kun Ding, Guancong Ma

As the counterpart of Hermitian nodal structures, the geometry formed by exceptional points (EPs), such as exceptional lines (ELs), entails intriguing spectral topology. We report the experimental realization of order-3 exceptional lines (EL3) that are entirely embedded in order-2 exceptional surfaces (ES2) in a three-dimensional periodic synthetic momentum

Avinash Amballa, Advaith P., Pradip Sasmal, Sumohana Channappayya

Training self-driving cars is often challenging since they require a vast amount of labeled data in multiple real-world contexts, which is computationally and memory intensive. Researchers often resort to driving simulators to train the agent and transfer the knowledge to a real-world setting. Since simulators lack realistic behavior, these methods are quite

Yuya Okawa, Taishi Kurahashi

We study the modal completeness and the finite frame property of several sublogics of the logic $\mathbf{IL}$ of interpretability with respect to Visser frames, which are also called simplified Veltman frames. Among other things, we prove that the logic $\mathbf{CL}$ of conservativity has the finite frame property with respect to that frames. This is an affi

Junyao Gao, Xinyang Jiang, Huishuai Zhang, Yifan Yang

While person Re-identification (Re-ID) has progressed rapidly due to its wide real-world applications, it also causes severe risks of leaking personal information from training data. Thus, this paper focuses on quantifying this risk by membership inference (MI) attack. Most of the existing MI attack algorithms focus on classification models, while Re-ID foll

Anil Kumar Karn

We introduce the notion of $\mathit{skeleton}$ with a head in a non-zero real vector space. We prove that skeletons with heads describe order unit spaces geometrically. Next, we consider the notion of $\mathit{periphery}$ corresponding to an order unit space which is a part of the skeleton. We note that periphery consists of boundary elements of the positive

Guangsen Wang, Shafiq Joty, Junnan Li, Steven Hoi

We introduce BotSIM, a modular, open-source Bot SIMulation environment with dialog generation, user simulation and conversation analytics capabilities. BotSIM aims to serve as a one-stop solution for large-scale data-efficient end-to-end evaluation, diagnosis and remediation of commercial task-oriented dialog (TOD) systems to significantly accelerate commerc

Zhiyu Tian

We give a geometric criterion to check the validity of the integral Tate conjecture for one-cycles on a smooth projective variety that is separably rationally connected in codimension one, and to check that the Brauer-Manin obstruction is the only obstruction to the local-global principle for zero-cycles on a separably rationally connected variety defined ov

Adithya Bhaskar, Alexander R. Fabbri, Greg Durrett

Large language models have shown impressive performance across a wide variety of tasks, including text summarization. In this paper, we show that this strong performance extends to opinion summarization. We explore several pipeline methods for applying GPT-3.5 to summarize a large collection of user reviews in a prompted fashion. To handle arbitrarily large

Benedikt Bollig, Alain Finkel, Amrita Suresh

We propose a relaxation to the definition of well-structured transition systems (\WSTS) while retaining the decidability of boundedness and non-termination. In this class, the well-quasi-ordered (wqo) condition is relaxed such that it is applicable only between states that are reachable one from another. Furthermore, the monotony condition is relaxed in the

Zheng Cao, Raymond Guo, Wenyu Du, Jiayi Gao

This paper introduced key aspects of applying Machine Learning (ML) models, improved trading strategies, and the Quasi-Reversibility Method (QRM) to optimize stock option forecasting and trading results. It presented the findings of the follow-up project of the research "Application of Convolutional Neural Networks with Quasi-Reversibility Method Results for

Zhiyu Tian

We prove a structural result about the space of one cycles of a separably rationally connected variety or a separably rationally connected fibration over a curve, either as a topological group or as an h-sheaf. This has the following consequences: a proof that the strong coniveau filtration agrees with the coniveau filtration on degree 3 homology, and a resu

Wang Liu, Cunhua Pan, Hong Ren, Feng Shu

Extremely large-scale reconfigurable intelligent surface (XL-RIS) has recently been proposed and is recognized as a promising technology that can further enhance the capacity of communication systems and compensate for severe path loss . However, the pilot overhead of beam training in XL-RIS-assisted wireless communication systems is enormous because the nea

Wensi Wang, Jiong Qiu, Rui Liu, Chunming Zhu

It is well established that solar eruptions are powered by free magnetic energy stored in current-carrying magnetic field in the corona. It has also been generally accepted that magnetic flux ropes (MFRs) are a critical component of many coronal mass ejections (CMEs). What remains controversial is whether MFRs are present well before the eruption. Our aim is

Jinghan Alina Hu, Meredith L. Rawls, Peter Yoachim, Željko Ivezić

We investigate a novel satellite avoidance strategy to mitigate the impact of large commercial satellite constellations in low-Earth orbit on the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We simulate the orbits of currently planned Starlink and OneWeb constellations ($\sim$40,000 satellites) to test how effectively an upgraded Rubin s

Quan-Lin Li, Yan-Xia Chang, Qing Wang

With rapid development of blockchain technology as well as integration of various application areas, performance evaluation, performance optimization, and dynamic decision in blockchain systems are playing an increasingly important role in developing new blockchain technology. This paper provides a recent systematic overview of this class of research, and es

Brandon Curd, Razieh Emami, Freek Roelofs, Richard Anantua

Tidal disruption events (TDEs) around super massive black holes (SMBHs) are a potential laboratory to study super-Eddington accretion disks and sometimes result in powerful jets or outflows which may shine in the radio and sub millimeter bands. In this work, we model the thermal synchrotron emission of jets from general relativistic radiation magneto-hydrody

Andrew McEntaggart, Alon E. Faraggi, Marco Guzzi

We consider $Z'$s in heterotic string derived models and study $Z'$ resonant production at the TeV scale at the Large Hadron Collider (LHC). We use various kinematic differential distributions for the Drell-Yan process at NNLO in QCD to explore the parameter space of such models and investigate $Z'$ couplings. In particular, we study the impact of $Z$-$Z'$ k

D Laavanya, S Devi Yamini

A graceful k-coloring of a non-empty graph $G=(V,E)$ is a proper vertex coloring $f:V(G)\rightarrow\lbrace 1,2,...,k \rbrace$, $k\geq 2$, which induces a proper edge coloring $f^{*}:E(G)\rightarrow\lbrace 1, 2, . . . , k-1 \rbrace $ defined by $f^{*}(uv) = |f(u)-f(v)|$, where $u,v\in V(G)$. The minimum $k$ for which $G$ has a graceful $k$-coloring is called

Adrien Poulenard, Maks Ovsjanikov, Leonidas J. Guibas

A wide range of techniques have been proposed in recent years for designing neural networks for 3D data that are equivariant under rotation and translation of the input. Most approaches for equivariance under the Euclidean group $\mathrm{SE}(3)$ of rotations and translations fall within one of the two major categories. The first category consists of methods

Qianzhong Chen, Sheng Cheng, Naira Hovakimyan

In this paper, we propose a framework for fast trajectory planning for unmanned aerial vehicles (UAVs). Our framework is reformulated from an existing bilevel optimization, in which the lower-level problem solves for the optimal trajectory with a fixed time allocation, whereas the upper-level problem updates the time allocation using analytical gradients. Th

Zichen He, Chunwei Song, Lu Dong

Safe and efficient co-planning of multiple robots in pedestrian participation environments is promising for applications. In this work, a novel multi-robot social-aware efficient cooperative planner that on the basis of off-policy multi-agent reinforcement learning (MARL) under partial dimension-varying observation and imperfect perception conditions is prop