November 2022 arXiv papers — page 158

Yanyang Li, Jianqiao Zhao, Michael R. Lyu, Liwei Wang

Recent advances in large-scale pre-training provide large models with the potential to learn knowledge from the raw text. It is thus natural to ask whether it is possible to leverage these large models as knowledge bases for downstream tasks. In this work, we answer the aforementioned question in unsupervised knowledge-grounded conversation. We explore vario

Ryan Mickler, Alexander Moll

In their study of Jack polynomials, Nazarov-Sklyanin introduced a remarkable new graded linear operator ${\mathcal L} \colon F[w] \rightarrow F[w]$ where $F$ is the ring of symmetric functions and $w$ is a variable. In this paper, we (1) establish a cyclic decomposition $F[w] \cong \bigoplus_{\lambda} Z(j_{\lambda}, {\mathcal L})$ into finite-dimensional ${\

Ao Zhang, Fan Yu, Kaixun Huang, Lei Xie

This paper summarizes the outcomes from the ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge (ICSRC). We first address the necessity of the challenge and then introduce the associated dataset collected from a new-energy vehicle (NEV) covering a variety of cockpit acoustic conditions and linguistic contents. We then describe the track arrangement

Kasidit Toprasertpong, Mitsuru Takenaka, Shinichi Takagi

A memory window of ferroelectric field-effect transistors (FeFETs), defined as a separation of the HIGH-state and the LOW-state threshold voltages, is an important measure of the FeFET memory characteristics. In this study, we theoretically investigate the relation between the FeFET memory window and the P-E hysteresis loop of the ferroelectric gate insulato

Xinyue Zhang, Genwang Wei, Ye Sheng, Jiong Yang

In the process of finding high-performance organic semiconductors (OSCs), it is of paramount importance in material development to identify important functional units that play key roles in material performance and subsequently establish substructure-property relationships. Herein, we describe a polymer-unit fingerprint (PUFp) generation framework. Machine l

Michael R. R. Good

Continuity across the shock wave of two regions in the metric during the formation of a black hole can be relaxed in order to achieve information preservation. A Planck scale sized spacetime discontinuity leads to unitarity (a constant asymptotic entanglement entropy) by restricting the origin of coordinates (moving mirror) to be timelike. Moreover, thermal

Nicolás Andruskiewitsch, Héctor Martín Peña Pollastri

We continue the study of the Drinfeld double of the Jordan plane, denoted by $\mathcal D$ and introduced in arXiv:2002.02514. The simple finite-dimensional modules were computed in arXiv:2108.13849; it turns out that they factorize through $U(\spl_2(\Bbbk))$. Here we introduce the Verma modules and the category $\mathfrak O$ for $\mathcal D$, which have a re

Chenyuan Wu, Bhavana Mehta, Mohammad Javad Amiri, Ryan Marcus

This paper presents AdaChain, a learning-based blockchain framework that adaptively chooses the best permissioned blockchain architecture in order to optimize effective throughput for dynamic transaction workloads. AdaChain addresses the challenge in the Blockchain-as-a-Service (BaaS) environments, where a large variety of possible smart contracts are deploy

Gaurav Kumar Nayak, Inder Khatri, Ruchit Rawal, Anirban Chakraborty

Several companies often safeguard their trained deep models (i.e., details of architecture, learnt weights, training details etc.) from third-party users by exposing them only as black boxes through APIs. Moreover, they may not even provide access to the training data due to proprietary reasons or sensitivity concerns. In this work, we propose a novel defens

Satoshi Naito, Daisuke Sagaki

The purpose of this paper is to prove a Pieri-type multiplication formula for quantum Grothendieck polynomials, which was conjectured by Lenart-Maeno. This formula would enable us to compute explicitly the quantum product of two arbitrary (opposite) Schubert classes in the (small) quantum $K$-theory ring $QK(Fl_{n})$ of the (full) flag manifold $Fl_{n}$ of t

Zongzhe Xu

This paper proposes a possible method using natural language processing that might assist in the FDA medical device marketing process. Actual device descriptions are taken and matched with the device description in FDA Title 21 of CFR to determine their corresponding device type. Both pre-trained word embeddings such as FastText and large pre-trained sentenc

Yizhu Jiao, Sha Li, Yiqing Xie, Ming Zhong

The argument role in event extraction refers to the relation between an event and an argument participating in it. Despite the great progress in event extraction, existing studies still depend on roles pre-defined by domain experts. These studies expose obvious weakness when extending to emerging event types or new domains without available roles. Therefore,

Zhutian Yang, Caelan Reed Garrett, Tomás Lozano-Pérez, Leslie Kaelbling

We present a learning-enabled Task and Motion Planning (TAMP) algorithm for solving mobile manipulation problems in environments with many articulated and movable obstacles. Our idea is to bias the search procedure of a traditional TAMP planner with a learned plan feasibility predictor. The core of our algorithm is PIGINet, a novel Transformer-based learning

Harsh Parikh

In this short note, I outline conditions under which conditioning on Synthetic Control (SC) weights emulates a randomized control trial where the treatment status is independent of potential outcomes. Specifically, I demonstrate that if there exist SC weights such that (i) the treatment effects are exactly identified and (ii) these weights are uniformly and

Irshaad Ahmed, Alberto Fiorenza, Maria Rosaria Formica, Amiran Gogatishvili

As in the work of Tartar ( Tartar L. Interpolation non lin\'eaire et r\'egularit\'e, 9, Journal of Functional Analysis, (1972), 469-489) we developed here some new results on non linear interpolation of $\alpha$-H\"olderian mappings between normed spaces, namely, by studying the action of the mappings on $K$-functionals and between interpolation spaces with

Felix Ma Yun, Jordan Nabi, Mitra Hassani

In a multi-input multi-output (MIMO) setup, where one side of the link comprises a linear antenna array, data can be transmitted over the direction of incident rays. Channel capacity for this setup is studied in this paper. We define two different setups; one when the energy is constant and equal over all rays, and one when available energy is evenly distrib

Hongxia Li, Zhongyi Cai, Jingya Wang, Jiangnan Tang

Federated learning is an emerging learning paradigm where multiple clients collaboratively train a machine learning model in a privacy-preserving manner. Personalized federated learning extends this paradigm to overcome heterogeneity across clients by learning personalized models. Recently, there have been some initial attempts to apply Transformers to feder

Li Li, Dongxing Xu, Haoran Wei, Yanhua Long

Exploiting effective target modeling units is very important and has always been a concern in end-to-end automatic speech recognition (ASR). In this work, we propose a phonetic-assisted multi target units (PMU) modeling approach, to enhance the Conformer-Transducer ASR system in a progressive representation learning manner. Specifically, PMU first uses the p

Jun Hashimoto, Hauyu Baobab Liu, Ruobing Dong, Beibei Liu

The azimuthal asymmetries of dust rings in protoplanetary disks such as a crescent around young stars are often interpreted as dust traps, and thus as ideal locations for planetesimal and planet formations. Whether such dust traps effectively promote planetesimal formation in disks around very-low-mass stars (VLM; a mass of $\lesssim$0.2~$M_\odot$) is debata

Angelo Kastroulis, Paolo Bonfini, Anastasios Litsas

Clinical Quality Language (CQL) has emerged as a standard for rule representation in Clinical Decision Support (CDS) and Electronic Clinical Quality Measurement (eCQM) in healthcare. While open-source reference implementations and a few commercial engines exist, there is still a market need for high-performance engines that can execute CQL queries on the sca

Raymundo Bautista, Efrén Pérez, Leonardo Salmerón

We give an intrinsic characterization of the closure under shifts $\widehat{\cal A}$ of a given strictly unital $A_\infty$-category ${\cal A}$. We study some arithmetical properties of its higher operations and special conflations in the precategory of cocycles ${\cal Z}({\cal A})$ of its $A_\infty$-category of twisted modules. We exhibit a structure for ${\

Ian Osband, Seyed Mohammad Asghari, Benjamin Van Roy, Nat McAleese

Language models often pre-train on large unsupervised text corpora, then fine-tune on additional task-specific data. However, typical fine-tuning schemes do not prioritize the examples that they tune on. We show that, if you can prioritize informative training data, you can achieve better performance while using fewer labels. To do this we augment a language

Tianao Li, Emma Alexander

Removing optical and atmospheric blur from galaxy images significantly improves galaxy shape measurements for weak gravitational lensing and galaxy evolution studies. This ill-posed linear inverse problem is usually solved with deconvolution algorithms enhanced by regularisation priors or deep learning. We introduce a so-called "physics-informed deep learnin

Roshan Thomas Eapen, Ramchander Rao Bhaskara, Manoranjan Majji

This paper presents Navigation and Rendering Pipeline for Astronautics (NaRPA) - a novel ray-tracing-based computer graphics engine to model and simulate light transport for space-borne imaging. NaRPA incorporates lighting models with attention to atmospheric and shading effects for the synthesis of space-to-space and ground-to-space virtual observations. In

Dániel Gerbner

We study the following problem. How many distinct copies of $H$ can an $n$-vertex graph $G$ have, if $G$ does not contain a rainbow $F$, that is, a copy of $F$ where each edge is contained in a different copy of $H$? The case $H=K_r$ is equivalent to the Tur\'an problem for Berge hypergraphs, which has attracted several researchers recently. We also explore

H. Xiong, L. Casagrande, X. Chen, J. Vos

Blue large-amplitude pulsators (BLAPs) are a newly discovered type of variable star. Their typical pulsation periods are on the order of a few tens of minutes, with relatively large amplitudes of 0.2-0.4 mag in optical bands, and their rates of period changes are on the order of $10^{-7} yr^{-1}$ (both positive and negative). They are extremely rare objects

Alberto Sainz Dalda, Bart De Pontieu

Observations by the Interface Region Imaging Spectrograph (IRIS) in the Mg II h & k spectral lines have provided a new diagnostic window towards the knowledge of the complex physical conditions in the solar chromosphere. Theoretical efforts focused on understanding the behavior of these lines have allowed us to obtain a better and more accurate vision of the

Peifeng Wang, Aaron Chan, Filip Ilievski, Muhao Chen

Neural language models (LMs) have achieved impressive results on various language-based reasoning tasks by utilizing latent knowledge encoded in their own pretrained parameters. To make this reasoning process more explicit, recent works retrieve a rationalizing LM's internal knowledge by training or prompting it to generate free-text rationales, which can be

Arpan Losalka, Jonathan Scarlett

We consider the problem of sequentially maximising an unknown function over a set of actions while ensuring that every sampled point has a function value below a given safety threshold. We model the function using kernel-based and Gaussian process methods, while differing from previous works in our assumption that the function is monotonically increasing wit

Yuan Tang, Wei Guo, Hiromichi Kobayashi, Satoshi Yui

Like many quantum fluids, superfluid helium-4 (He II) can be considered as a mixture of two miscible fluid components: an inviscid superfluid and a viscous normal fluid consisting of thermal quasiparticles [1]. A mutual friction between the two fluids can emerge due to quasiparticles scattering off quantized vortex lines in the superfluid [2]. This quantum d

Yifan Gao, Danni Zhang, Haoyue Li

The game of Go has been highly under-researched due to the lack of game records and analysis tools. In recent years, the increasing number of professional competitions and the advent of AlphaZero-based algorithms provide an excellent opportunity for analyzing human Go games on a large scale. In this paper, we present the ProfessionAl Go annotation datasEt (P

David Damanik, Mark Embree, Jake Fillman

Inspired by the 1995 paper of Baake--Grimm--Pisani, we aim to explain the empirical observation that the distribution of Lee--Yang zeros corresponding to a one-dimensional Ising model appears to follow the gap labelling theorem. This follows by combining two main ingredients: first, the relation between the transfer matrix formalism for 1D Ising model and an

Chris Muris, Konstantin Wacker

This paper analyzes how interaction effects can be consistently estimated under economically plausible assumptions in linear panel models with a fixed $T$-dimension. We advocate for a \emph{correlated interaction term estimator} (CITE) and show that it is consistent under conditions that are not sufficient for consistency of the interaction term estimator th

Fan Yang, Xinhao Xu, Hui Chen, Yuchen Guo

The ground plane prior is a very informative geometry clue in monocular 3D object detection (M3OD). However, it has been neglected by most mainstream methods. In this paper, we identify two key factors that limit the applicability of ground plane prior: the projection point localization issue and the ground plane tilt issue. To pick up the ground plane prior

Joachim König

Continuing the line of thought of an earlier work, we provide the first infinite family of quadratic number fields with everywhere unramified Galois extensions of Galois group $SL_2(5)$, the (unique) smallest nonsolvable group for which this problem was previously open. Our approach also improves upon previous work by yielding the first infinite family of re

Ruoxi Jiang, Rebecca Willett

This paper explores learning emulators for parameter estimation with uncertainty estimation of high-dimensional dynamical systems. We assume access to a computationally complex simulator that inputs a candidate parameter and outputs a corresponding multichannel time series. Our task is to accurately estimate a range of likely values of the underlying paramet

Lu Ying, Aoyu Wu, Haotian Li, Zikun Deng

Visual analytics (VA) systems have been widely used in various application domains. However, VA systems are complex in design, which imposes a serious problem: although the academic community constantly designs and implements new designs, the designs are difficult to query, understand, and refer to by subsequent designers. To mark a major step forward in tac

Ruyuan Wan, Naome Etori, Karla Badillo-Urquiola, Dongyeop Kang

The bridging research between Human-Computer Interaction and Natural Language Processing is developing quickly these years. However, there is still a lack of formative guidelines to understand the human-machine interaction in the NLP loop. When researchers crossing the two fields talk about humans, they may imply a user or labor. Regarding a human as a user,

Yucheng Wang

Conventionally the mobility edge (ME) separating extended states from localized ones is a central concept in understanding Anderson localization transition. The critical state, being delocalized and non-ergodic, is a third type of fundamental state that is different from both the extended and localized states. Here we study the localization phenomena in a on

Faisal Tareque Shohan, Abu Ubaida Akash, Muhammad Ibrahim, Mohammad Shafiul Alam

Crime is an unlawful act that carries legal repercussions. Bangladesh has a high crime rate due to poverty, population growth, and many other socio-economic issues. For law enforcement agencies, understanding crime patterns is essential for preventing future criminal activity. For this purpose, these agencies need structured crime database. This paper introd

Fermin Cuevas, Barbara Laïk, Junxian Zhang, Mickaël Mateos

Lithium-ion batteries (LiBs) based on insertion electrodes reach intrinsic capacity limits. Performance improvements and cost reduction require alternative reaction mechanisms and novel battery chemistries such as conversion reactions and sodium-ion batteries (NaBs), respectively. We here study the formation of Ti1-xVxH2 hydrides (0 < x < 1) and their electr

Lei Fu, Huanle Zhang, Ge Gao, Mi Zhang

As a privacy-preserving paradigm for training Machine Learning (ML) models, Federated Learning (FL) has received tremendous attention from both industry and academia. In a typical FL scenario, clients exhibit significant heterogeneity in terms of data distribution and hardware configurations. Thus, randomly sampling clients in each training round may not ful

Tien-Cuong Bui, Van-Duc Le, Wen-Syan Li, Sang Kyun Cha

Graph Neural Networks (GNNs) are widely used in many modern applications, necessitating explanations for their decisions. However, the complexity of GNNs makes it difficult to explain predictions. Even though several methods have been proposed lately, they can only provide simple and static explanations, which are difficult for users to understand in many sc

John Cai, Weinan Wang

To effectively optimize and personalize treatments, it is necessary to investigate the heterogeneity of treatment effects. With the wide range of users being treated over many online controlled experiments, the typical approach of manually investigating each dimension of heterogeneity becomes overly cumbersome and prone to subjective human biases. We need an

Sergei V. Ketov, Ekaterina O. Pozdeeva, Sergey Yu. Vernov

Superstring/M-theory is the theory of quantum gravity that can provide the UV-completion to viable inflation models. We modify the Starobinsky inflation model by adding the Bel-Robinson tensor $T^{\mu\nu\lambda\rho}$ squared term proposed as the leading quantum correction inspired by superstring theory. The $(R+\frac{1}{6m^2}R^2 -\frac{\beta}{8m^6}T^2)$ mode

Huidan Xiao, Tao Yang

In the field of urban planning, road network system planning is often the first step and the main purpose of urban planning is to create a spatial configuration of different functions such as residence, education, business, etc. Generally speaking, the more mixed the functions of an area has, the more possible its vitality may be. Therefore, in this article,

Jorge Martínez, David Meza-Alcántara, Carlos Uzcátegui

We address some phenomena about the interaction between lower semicontinuous submeasures on $\mathbb{N}$ and $F_{\sigma}$ ideals. We analyze the pathology degree of a submeasure and present a method to construct pathological $F_\sigma$ ideals. We give a partial answers to the question of whether every nonpathological tall $F_\sigma$ ideal is Kat\v{e}tov abov

Huayang Song, Xia Wan, Jiang-Hao Yu

The new measurement of the W boson mass from the CDF collaboration shows a significant tension with the Standard Model prediction, which evidences violation of custodial symmetry in the scalar sector. We study the scalar extensions of the Standard Model, which can be categorized into two classes, scalar sector with custodial symmetry (Georgi-Machacek model a

Shuhao Gu, Bojie Hu, Yang Feng

This paper considers continual learning of large-scale pretrained neural machine translation model without accessing the previous training data or introducing model separation. We argue that the widely used regularization-based methods, which perform multi-objective learning with an auxiliary loss, suffer from the misestimate problem and cannot always achiev

G. Gonzalez, H. C. Rosu, O. Perez-Cornejo, S. C. Mancas

For the case of nonlinear second-order differential equations with a constant coefficient of the first derivative term and polynomial nonlinearities, the factorization conditions of Rosu and Cornejo-Perez are approached in two ways: (i) by commuting the subindices of the factorization functions in the two factorization conditions and (ii) by leaving invarian

H. Tong

The magnetar SGR 1935+2154 is reported to have an anti-glitch, accompanied by fast radio bursts, and transient pulsed radio emission. In the wind braking model, this triplet event tells people that (1) SGR 1935+2154 does not have a strong particle wind and can be approximated by magnetic dipole braking in the persistent state; (2) Its anti-glitch is due to a

Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, George J. Pappas

We are interested in predicting failures of cyber-physical systems during their operation. Particularly, we consider stochastic systems and signal temporal logic specifications, and we want to calculate the probability that the current system trajectory violates the specification. The paper presents two predictive runtime verification algorithms that predict

Hao Xu, Peize Liu, Xinyi Chen, Shaojie Shen

Collaborative simultaneous localization and mapping (CSLAM) is essential for autonomous aerial swarms, laying the foundation for downstream algorithms such as planning and control. To address existing CSLAM systems' limitations in relative localization accuracy, crucial for close-range UAV collaboration, this paper introduces $D^2$SLAM-a novel decentralized

Toru Kitagawa, Hugo Lopez, Jeff Rowley

This paper proposes a novel method to estimate individualised treatment assignment rules. The method is designed to find rules that are stochastic, reflecting uncertainty in estimation of an assignment rule and about its welfare performance. Our approach is to form a prior distribution over assignment rules, not over data generating processes, and to update

Bhavya Agrawalla, Nasief Khlaif, Haynes Miller

We observe that Beck modules for a commutative monoid are exactly modules over a graded commutative ring associated to the monoid. Under this identification, the Quillen cohomology of commutative monoids is a special case of Andr\'e-Quillen cohomology for graded commutative rings, generalizing a result of Kurdiani and Pirashvili. To verify this we develop th

Lionel Nganyewou Tidjon, Foutse Khomh

Increasingly, malwares are becoming complex and they are spreading on networks targeting different infrastructures and personal-end devices to collect, modify, and destroy victim information. Malware behaviors are polymorphic, metamorphic, persistent, able to hide to bypass detectors and adapt to new environments, and even leverage machine learning technique

Chengqun Yang, Ling Zhu, Behzad Tahmasebzadeh, Xiang-Xiang Xue

The halo stars on highly radial orbits should inevitably pass the center regions of the Milky Way. Under the assumption that the stellar halo is in dynamical equilibrium and axisymmetric, we integrate the orbits of $\sim 10,000$ halo K-giants at $5\leq r \leq 50$ kpc cross-matched from LAMOST DR5 and $Gaia$ DR3. By carefully considering the selection functio

Patrick Tinsley, Adam Czajka, Patrick Flynn

Generative Adversarial Networks (GANs) have proven to be a preferred method of synthesizing fake images of objects, such as faces, animals, and automobiles. It is not surprising these models can also generate ISO-compliant, yet synthetic iris images, which can be used to augment training data for iris matchers and liveness detectors. In this work, we trained

Pandeng Cao, Hongjun Li

On a Hermitian manifold, the Chern connection can induce a metric connection on the background Riemannian manifold. We call the sectional curvature of the metric connection induced by the Chern connection the Chern sectional curvature of this Hermitian manifold. First, we derive expression of the Chern sectional curvature in local complex coordinates. As an

Amaury Perrocheau, Thomas M. Esposito, Paul A. Dalba, Franck Marchis

More than 5,000 exoplanets have been confirmed and among them almost 4,000 were discovered by the transit method. However, few transiting exoplanets have an orbital period greater than 100 days. Here we report a transit detection of Kepler-167 e, a "Jupiter analog" exoplanet orbiting a K4 star with a period of 1,071 days, using the Unistellar ground-based te

Juntao Huang, Wei Guo, Yingda Cheng

This paper reviews the adaptive sparse grid discontinuous Galerkin (aSG-DG) method for computing high dimensional partial differential equations (PDEs) and its software implementation. The C\texttt{++} software package called AdaM-DG, implementing the aSG-DG method, is available on Github at \url{https://github.com/JuntaoHuang/adaptive-multiresolution-DG}. T

Sourav Pal, Prajakta Sahasrabuddhe, Nitin Tomar

In the literature, we have several results associated with canonical decomposition of commuting contractions. In this paper, we generalize a few of these results to $Q$-commuting contractions. Here we mainly deal with $Q$-commuting and doubly $Q$-commuting contractions when $Q$ is a family of unitary operators.

Oscar Domínguez, Sergey Tikhonov

We introduce truncated Besov and Triebel--Lizorkin function spaces and investigate their main properties: embeddings, interpolation, duality, lifting, traces. These new scales allow us to improve several known results in functional analysis and PDE's.

Ruicheng Xian, Lang Yin, Han Zhao

To mitigate the bias exhibited by machine learning models, fairness criteria can be integrated into the training process to ensure fair treatment across all demographics, but it often comes at the expense of model performance. Understanding such tradeoffs, therefore, underlies the design of fair algorithms. To this end, this paper provides a complete charact

J. Brian Burns, Aravind Sundaresan, Pedro Sequeira, Vidyasagar Sadhu

We present an approach for autonomous sensor control for information gathering under partially observable, dynamic and sparsely sampled environments that maximizes information about entities present in that space. We describe our approach for the task of Radio-Frequency (RF) spectrum monitoring, where the goal is to search for and track unknown, dynamic sign

R. K. Cochrane, C. C. Hayward, D. Anglés-Alcázar

Single flux density measurements at observed-frame sub-millimeter and millimeter wavelengths are commonly used to probe dust and gas masses in galaxies. In this Letter, we explore the robustness of this method to infer dust mass, focusing on quiescent galaxies, using a series of controlled experiments on four massive haloes from the Feedback in Realistic Env

Abhay Ashtekar

Exactly soluble models can serve as excellent tools to explore conceptual issues in non-perturbative quantum gravity. In perturbative approaches, it is only the two radiative modes of the linearized gravitational field that are quantized. The goal of this investigation is to probe the `Coulombic' aspects of quantum geometry that are governed entirely by matt

Anna Muranova

We consider a dual Cheeger constant $\overline h$ for finite graphs with edge weights from an arbitrary real-closed ordered field. We obtain estimates of $\overline h$ in terms of number of vertices in graph. Further, we estimate the largest eigenvalue for the discrete Laplace operator in terms of $\overline h$ and show the sharpness of estimates. As an exam

Sijia Xiao, Shagun Jhaver, Niloufar Salehi

Most social media platforms implement content moderation to address interpersonal harms such as harassment. Content moderation relies on offender-centered, punitive approaches, e.g., bans and content removal. We consider an alternative justice framework, restorative justice, which aids victims in healing, supports offenders in repairing the harm, and engages

Alexander Kunkel, Tzihong Chiueh, Björn Malte Schäfer

We investigate nonlinear structure formation in the fuzzy dark matter (FDM) model in comparison to cold dark matter (CDM) models from a weak lensing perspective using perturbative methods. We use Eulerian perturbation theory (PT) up to fourth order to compute the tree-level matter trispectrum and the one-loop matter spectrum and bispectrum from consistently

Yonggan Fu, Yang Zhang, Kaizhi Qian, Zhifan Ye

Self-supervised learning (SSL) for rich speech representations has achieved empirical success in low-resource Automatic Speech Recognition (ASR) and other speech processing tasks, which can mitigate the necessity of a large amount of transcribed speech and thus has driven a growing demand for on-device ASR and other speech processing. However, advanced speec

Arkajyoti Saha, Daniela Witten, Jacob Bien

We consider testing whether a set of Gaussian variables, selected from the data, is independent of the remaining variables. We assume that this set is selected via a very simple approach that is commonly used across scientific disciplines: we select a set of variables for which the correlation with all variables outside the set falls below some threshold. Un

Paraskevi Nousi, Alexandra E. Koloniari, Nikolaos Passalis, Panagiotis Iosif

Traditionally, gravitational waves are detected with techniques such as matched filtering or unmodeled searches based on wavelets. However, in the case of generic black hole binaries with non-aligned spins, if one wants to explore the whole parameter space, matched filtering can become impractical, which sets severe restrictions on the sensitivity and comput

Ashish Seth, Sreyan Ghosh, S. Umesh, Dinesh Manocha

We present a new Self-Supervised Learning (SSL) approach to pre-train encoders on unlabeled audio data that reduces the need for large amounts of labeled data for audio and speech classification. Our primary aim is to learn audio representations that can generalize across a large variety of speech and non-speech tasks in a low-resource un-labeled audio pre-t

Diego Martinez-Taboada, Dino Sejdinovic

The counterfactual distribution models the effect of the treatment in the untreated group. While most of the work focuses on the expected values of the treatment effect, one may be interested in the whole counterfactual distribution or other quantities associated to it. Building on the framework of Bayesian conditional mean embeddings, we propose a Bayesian

Jiajie Guo, Lucas Q. Flagg, Duyen K. Tran, Shinya E. Chen

We study the organic electrochemical transistors (OECTs) performance of the ladder polymer, poly(benzimidazobenzophenanthroline) (BBL) in an attempt to better understand how an apparently hydrophobic side-chain-free polymer is able to operate as an OECT with favorable redox kinetics in an aqueous environment. We examine two BBLs of different molecular masses

A. C. Caligula do E. S. Pedreira, N. Fraija, A. Galvan-Gamez, B. Betancourt Kamenetskaia

As we further our studies on Gamma-ray bursts (GRBs), both on theoretical models and observational tools, more and more options begin to open for exploration of its physical properties. As transient events primarily dominated by synchrotron radiation, it is expected that the synchrotron photons emitted by GRBs should present some degree of polarization throu

Sreyan Ghosh, Ashish Seth, S. Umesh, Dinesh Manocha

We present Multiscale Audio Spectrogram Transformer (MAST) for audio classification, which brings the concept of multiscale feature hierarchies to the Audio Spectrogram Transformer (AST). Given an input audio spectrogram, we first patchify and project it into an initial temporal resolution and embedding dimension, post which the multiple stages in MAST progr

Nicholas Rivera, Jamison Sloan, Yannick Salamin, John D. Joannopoulos

The quantization of the electromagnetic field leads directly to the existence of quantum mechanical states, called Fock states, with an exact integer number of photons. Despite these fundamental states being long-understood, and despite their many potential applications, generating them is largely an open problem. For example, at optical frequencies, it is c

Qiangqiang Huang, Joseph DeGol, Victor Fragoso, Sudipta N. Sinha

Adding fiducial markers to a scene is a well-known strategy for making visual localization algorithms more robust. Traditionally, these marker locations are selected by humans who are familiar with visual localization techniques. This paper explores the problem of automatic marker placement within a scene. Specifically, given a predetermined set of markers a

Kaylee Yingxi Yang, Andre Wibisono

Motivated by the increasingly popular Score-based Generative Modeling (SGM), we study the Inexact Langevin Dynamics (ILD) and Inexact Langevin Algorithm (ILA) where a score function estimate is used in place of the exact score. We establish {\em stable} biased convergence guarantees in terms of the Kullback-Leibler (KL) divergence. To achieve these guarantee

Özgün Arslan, Seyit Hocuk, Paola Caselli, İbrahim Küçük

In molecular cloud cores, the cosmic ray (CR) induced sputtering via CR ion-icy grain collision is one of the desorption processes for ice molecules from mantles around dust grains. The efficiency of this process depends on the incident CR ion properties as well as the physicochemical character of the ice mantle. Our main objective is the examination of the

Henry Bradford, Francesco Fournier-Facio

We study the Hopf property for wreath products of finitely generated groups, focusing on the case of an abelian base group. Our main result establishes a strong connection between this problem and Kaplansky's stable finiteness conjecture. Namely, the latter holds true if and only if for every finitely generated abelian group $A$ and every finitely generated

Alessandro Verra

After an Introduction to the themes of Enriques surfaces and Rationality questions, the Artin-Mumford counterexample to Lueroth problem is revisited. A construction of it is given, which is related in an explicit way to the geometry of Enriques surfaces, more precisely to the special family of Reye congruences and their classical geometry.

Narges Khakpour, David Parker

Network systems often contain vulnerabilities that remain unfixed in a network for various reasons, such as the lack of a patch or knowledge to fix them. With the presence of such residual vulnerabilities, the network administrator should properly react to the malicious activities or proactively prevent them, by applying suitable countermeasures that minimiz

Song-Ying Li

In this paper, the author solves the long term open problem of Kerzman on sup-norm estimate for Cauchy-Riemann equation on polydisc in $n$-dimensional complex space. The problem has been open since 1971. He also extends and solves the problem on a bounded product domain $\Omega^n$, where $\Omega$ either is simply connected with $C^{1,\alpha}$ boundary or sat

Ziming Shao, Noah Schnitzer, Jacob Ruf, Oleg Y. Gorobtsov

Exploiting the emerging nanoscale periodicities in epitaxial, single-crystal thin films is an exciting direction in quantum materials science: confinement and periodic distortions induce novel properties. The structural motifs of interest are ferroelastic, ferroelectric, multiferroic, and, more recently, topologically protected magnetization and polarization

Minjie Lei, Ka Vang Tsang, Sean Gasiorowski, Chuan Li

Optical photons are used as signal in a wide variety of particle detectors. Modern neutrino experiments employ hundreds to tens of thousands of photon detectors to observe signal from millions to billions of scintillation photons produced from energy deposition of charged particles. These neutrino detectors are typically large, containing kilotons of target

Lige Zhang, Yi-Nong Rao

An accurate and detailed field map is important for cyclotron beam dynamics studies. During the long history of cyclotron studies, many techniques have been developed by cyclotron pioneers for the treatment of median plane field map. In this paper, we take the TRIUMF 500 MeV cyclotron as an example to study the asymmetric field resulting from the imperfect m

Renato Pelessoni, Paolo Vicig

We investigate how basic probability inequalities can be extended to an imprecise framework, where (precise) probabilities and expectations are replaced by imprecise probabilities and lower/upper previsions. We focus on inequalities giving information on a single bounded random variable $X$, considering either convex/concave functions of $X$ (Jensen's inequa

Audrey Chatain, Alice Le Gall, Jean-Jacques Berthelier, Ralph D. Lorenz

The EFIELD instrument is part of the geophysics and meteorology sensor package DraGMet on the Dragonfly mission, which will explore the surface of Titan in the mid-2030s. EFIELD consists of two electrodes designed to passively record the AC electric field at each landing site. The exploration zone of Dragonfly will mostly consist of dune fields, covered with

H. Ning, O. Mehio, C. Lian, X. Li

Elemental tellurium is a strongly spin-orbit coupled Peierls-distorted semiconductor whose band structure features topologically protected Weyl nodes. Using time-dependent density functional theory calculations, we show that impulsive optical excitation can be used to transiently control the amplitude of the Peierls distortion, realizing a mechanism to switc

Wenxuan Zhou, David Held

A simple gripper can solve more complex manipulation tasks if it can utilize the external environment such as pushing the object against the table or a vertical wall, known as "Extrinsic Dexterity." Previous work in extrinsic dexterity usually has careful assumptions about contacts which impose restrictions on robot design, robot motions, and the variations

Spilios Evmorfos, Athina P. Petropulu, H. Vincent Poor

The paper studies the problem of designing the Intelligent Reflecting Surface (IRS) phase shifters for Multiple Input Single Output (MISO) communication systems in spatiotemporally correlated channel environments, where the destination can move within a confined area. The objective is to maximize the expected sum of SNRs at the receiver over infinite time ho

Ming Zhou, Andrew V. Knyazev, Klaus Neymeyr

Convergence rates of block iterations for solving eigenvalue problems typically measure errors of Ritz values approximating eigenvalues. The errors of the Ritz values are commonly bounded in terms of principal angles between the initial or iterative subspace and the invariant subspace associated with the target eigenvalues. Such bounds thus cannot be applied

Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney

Interpretable and explainable machine learning has seen a recent surge of interest. We focus on safety as a key motivation behind the surge and make the relationship between interpretability and safety more quantitative. Toward assessing safety, we introduce the concept of maximum deviation via an optimization problem to find the largest deviation of a super

X. Dai, R. Trappen, R. Yang, S. M. Disseler

Flux tunability is an important engineering resource for superconducting circuits. Large-scale quantum computers based on flux-tunable superconducting circuits face the problem of flux crosstalk, which needs to be accurately calibrated to realize high-fidelity quantum operations. Typical calibration methods either assume that circuit elements can be effectiv

Yu Zhang, Mitchell Bucklew

In this paper, we introduce Max Markov Chain (MMC), a novel representation for a useful subset of High-order Markov Chains (HMCs) with sparse correlations among the states. MMC is parsimony while retaining the expressiveness of HMCs. Even though parameter optimization is generally intractable as with HMC approximate models, it has an analytical solution, bet

Connor Albright, Kimberly P. Hadaway, Ari Holcombe Pomerance, Joel Jeffries

In a connected graph, Kemeny's constant gives the expected time of a random walk from an arbitrary vertex $x$ to reach a randomly-chosen vertex $y$. Because of this, Kemeny's constant can be interpreted as a measure of how well a graph is connected. It is generally unknown how the addition or removal of edges affects Kemeny's constant. Inspired by the direct

Aijun Bai, Rolf Jagerman, Zhen Qin, Le Yan

As Learning-to-Rank (LTR) approaches primarily seek to improve ranking quality, their output scores are not scale-calibrated by design. This fundamentally limits LTR usage in score-sensitive applications. Though a simple multi-objective approach that combines a regression and a ranking objective can effectively learn scale-calibrated scores, we argue that th