February 2024 arXiv papers — page 72

Adam Siegel, Armands Strikis, Michael Fogarty

It is well understood that a two-dimensional grid of locally-interacting qubits is a promising platform for achieving fault tolerant quantum computing. However in the near-future, it may prove less challenging to develop lower dimensional structures. In this paper, we show that such constrained architectures can also support fault tolerance; specifically we

Kartik Sheth, Kevin Govender, Vanessa McBride, Laura Trouille

Policy Brief on "Workforce Development in Astronomy and Astroinformatics", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. The discipline of astronomy and astroinformatics is dynamically evolving thereby creating a compelling opportunity t

Giovanni De Felice, Andrea Cini, Daniele Zambon, Vladimir V. Gusev

Virtual sensing techniques allow for inferring signals at new unmonitored locations by exploiting spatio-temporal measurements coming from physical sensors at different locations. However, as the sensor coverage becomes sparse due to costs or other constraints, physical proximity cannot be used to support interpolation. In this paper, we overcome this challe

Ravindra Kumar Yadav, Sitakanta Satapathy, Prathmesh Deshmukh, Biswajit Datta

Realizing lattices of exciton polariton condensates has been of much interest owing to the potential of such systems to realize analog Hamiltonian simulators and physical computing architectures. Prior work on polariton condensate lattices has primarily been on GaAs-based systems, with the recent advent of organic molecules and perovskite systems allowing ro

Ralf Konietzka, Alyssa A. Goodman, Catherine Zucker, Andreas Burkert

Our Sun lies within 300 pc of the 2.7-kpc-long sinusoidal chain of dense gas clouds known as the Radcliffe Wave. The structure's wave-like shape was discovered using 3D dust mapping, but initial kinematic searches for oscillatory motion were inconclusive. Here we present evidence that the Radcliffe Wave is oscillating through the Galactic plane while also dr

Kazem Izadinasab, Ahmed Wagdy Shaban, Oussama Damen

In this paper, we propose a deep learning (DL)-based approach for efficiently computing the inverse of Hermitian matrices using truncated polynomial expansion (TPE). Our model-driven approach involves optimizing the coefficients of the TPE during an offline training procedure for a given number of TPE terms. We apply this method to signal detection in uplink

S. Bradley Cenko, Richard Doyle, Daniel Crichton, Seetha Somasundaram

Policy Brief on "Long Term Space Data and Informatics Needs", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Persistent space data gathering, retention, transmission, and analysis play a pivotal role in deepening our grasp of the Universe

Joseph Marvin Imperial, Gail Forey, Harish Tayyar Madabushi

Domain experts across engineering, healthcare, and education follow strict standards for producing quality content such as technical manuals, medication instructions, and children's reading materials. However, current works in controllable text generation have yet to explore using these standards as references for control. Towards this end, we introduce Stan

Marco Bravin, Francesco Fanelli

In this paper, we study the global solvability of the density-dependent incompressible Euler equations, supplemented with a damping term of the form $ \mathfrak{D}_{\alpha}^{\gamma}(\rho, u) = \alpha \rho^{\gamma} u $, where $\alpha>0$ and $ \gamma \in \{0,1\} $. To some extent, this system can be seen as a simplified model describing the mean dynamics in th

Anthony Brown, Federica Bianco, Varun Bhalerao, Shri Kulkarni

Policy Brief on "Latest Developments and Opportunities in Sky Survey", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Sky surveys have been a crucial tool in advancing our understanding of the Universe. The last few decades have seen an e

Mohsen Yarmohammadi, John Sous, Marin Bukov, Michael H. Kolodrubetz

We study the effect of a terahertz field-driven single cavity mode for ultrafast control of a fermion chain with dissipation-induced nonlinearity and quadratic coupling to an infrared-active phonon mode. Without photon loss from the cavity, we uncover a first-order phase transition in the nonequilibrium steady state only for the lower phonon-polariton, accom

Sonja Johnson-Yu, Nicholas Bowman, Mehran Sahami, Chris Piech

While the use of programming problems on exams is a common form of summative assessment in CS courses, grading such exam problems can be a difficult and inconsistent process. Through an analysis of historical grading patterns we show that inaccurate and inconsistent grading of free-response programming problems is widespread in CS1 courses. These inconsisten

David Leslie, Cami Rincon, Morgan Briggs, Antonella Perini

Reaching consensus on a commonly accepted definition of AI Fairness has long been a central challenge in AI ethics and governance. There is a broad spectrum of views across society on what the concept of fairness means and how it should best be put to practice. In this workbook, we tackle this challenge by exploring how a context-based and society-centred ap

Shiyang Lai, Yujin Potter, Junsol Kim, Richard Zhuang

Large language model behavior is shaped by the language of those with whom they interact. This capacity and their increasing prevalence online portend that they will intentionally or unintentionally "program" one another and form emergent AI subjectivities, relationships, and collectives. Here, we call upon the research community to investigate these "societ

David Leslie, Cami Rincon, Morgan Briggs, Antonella Perini

The sustainability of AI systems depends on the capacity of project teams to proceed with a continuous sensitivity to their potential real-world impacts and transformative effects. Stakeholder Impact Assessments (SIAs) are governance mechanisms that enable this kind of responsiveness. They are tools that create a procedure for, and a means of documenting, th

Kiril Bangachev, Guy Bresler

The random geometric graph $\mathsf{RGG}(n,\mathbb{S}^{d-1}, p)$ is formed by sampling $n$ i.i.d. vectors $\{V_i\}_{i = 1}^n$ uniformly on $\mathbb{S}^{d-1}$ and placing an edge between pairs of vertices $i$ and $j$ for which $\langle V_i,V_j\rangle \ge \tau^p_d,$ where $\tau^p_d$ is such that the expected density is $p.$ We study the low-degree Fourier coef

David Leslie, Cami Rincon, Morgan Briggs, Antonella Perini

Sustainable AI projects are continuously responsive to the transformative effects as well as short-, medium-, and long-term impacts on individuals and society that the design, development, and deployment of AI technologies may have. Projects, which centre AI Sustainability, ensure that values-led, collaborative, and anticipatory reflection both guides the as

Ingrid Torres, Alex Krasnok

Twistronics, originally conceptualized within the electronics domain to modulate electronic properties through the twist angle between stacked two-dimensional (2D) materials, presents a groundbreaking approach in material science. This concept's extension to photonics, especially using metasurfaces, offers a promising avenue for manipulating light at subwave

Reinhard M. Grassmann, Anastasiia Senyk, Jessica Burgner-Kahrs

Concentric tube continuum robots utilize nested tubes, which are subject to a set of inequalities. Current approaches to account for inequalities rely on branching methods such as if-else statements. It can introduce discontinuities, may result in a complicated decision tree, has a high wall-clock time, and cannot be vectorized. This affects the behavior and

David Leslie, Cami Rincon, Morgan Briggs, Antonella Perini

AI systems may have transformative and long-term effects on individuals and society. To manage these impacts responsibly and direct the development of AI systems toward optimal public benefit, considerations of AI ethics and governance must be a first priority. In this workbook, we introduce and describe our PBG Framework, a multi-tiered governance model tha

Nicholas M. Hougland, Zhuan Li, Ryan Kaufman, Boris Mesits

Circuit QED based quantum information processing relies on low noise amplification for signal readout. In the realm of microwave superconducting circuits, this amplification is often achieved via Josephson parametric amplifiers (JPA). In the past, these amplifiers exhibited low power added efficiency (PAE), which is roughly the fraction of pump power that is

Sebastian Zapata

In the search for transverse-universal knots in the standard contact structure on $\mathbb{S}^3$, we present a classification of the transverse twist knots with maximal self-linking number, that admit only overtwisted contact branched covers. As a direct consequence, we obtain an infinite family of transverse knots in $(\mathbb{S}^3,\xi_{std})$ that are not

Sahasrajit Sarmasarkar, Harish Pillai

We consider the problem of job assignment where a master server aims to compute some tasks and is provided a few child servers to compute under a uniform straggling pattern where each server is equally likely to straggle. We distribute tasks to the servers so that the master is able to receive most of the tasks even if a significant number of child servers f

Sina Akbari, Negar Kiyavash

The renowned difference-in-differences (DiD) estimator relies on the assumption of 'parallel trends,' which does not hold in many practical applications. To address this issue, the econometrics literature has turned to the triple difference estimator. Both DiD and triple difference are limited to assessing average effects exclusively. An alternative avenue i

Ioann Vasilyev

The condition mentioned in the title is equivalent to the representability of $f$ as the quotient $f=v_1/v_2$, where $v_1$ and $v_2$ obey the inequalities $|R_j v_i| \leq C |v_i|$ for $i=1,2$ and $j=1,\ldots, n$. Here, $R_1,\ldots, R_n$ are the Riesz transformations.

Ioann Vasilyev

In this paper K closedness is proved in the case of the couple of real Hardy spaces in the corresponding couple of Lebesgue spaces. This means roughly that any measurable decomposition of an analytic function gives rise to an "analytic" decomposition with summands of roughly the same size. The proof uses Bourgain's method, the atomic decomposition for Hardy

Arjun Krishnan, Sevak Mkrtchyan, Scott Neville

In dimensions 3 or larger, it is a classical fact that the directed polymer model has two phases: Brownian behavior at high temperature, and non-Brownian behavior at low temperature. We consider the response of the polymer to an external field or tilt, and show that at fixed temperature, the polymer has Brownian behavior for some fields and non-Brownian beha

Joanna Kułaga-Przymus, Michał D. Lemańczyk, Michał Rams

Consider a partial order on $\{0,1\}^{\mathbb Z}: x\leq y$ when $x_i\leq y_i$ for all $i\in\mathbb{Z}$. A subshift $X\subset\{0,1\}^{\mathbb{Z}}$ is hereditary if together with any $x\in \{0,1\}^{\mathbb Z}$ it contains all $y\leq x$. Heuristically speaking, a hereditary subshift contains all the elements between maximal elements (with respect to this partia

Wolfgang Wieland

Recently, we introduced a non-perturbative quantization of impulsive gravitational null initial data. In this note, we investigate an immediate physical implication of the model. One of the quantum numbers is the total luminosity carried to infinity. We show that a transition happens when the luminosity reaches the Planck power $\mathcal{L}_{\mathrm{P}}$. Be

Roy Shadmon, Daniel Spencer, Owen Arden

Distributed control systems require high reliability and availability guarantees despite often being deployed at the edge of network infrastructure. Edge computing resources are less secure and less reliable than centralized resources in data centers. Replication and consensus protocols improve robustness to network faults and crashed or corrupted nodes, but

Julia C. Thome, Peter F. Rebeiro, Andrew J. Spieker, Bryan E. Shepherd

While a randomized control trial is considered the gold standard for estimating causal treatment effects, there are many research settings in which randomization is infeasible or unethical. In such cases, researchers rely on analytical methods for observational data to explore causal relationships. Difference-in-differences (DID) is one such method that, mos

Enrique Ide

I examine how upstream mergers affect negotiated prices when suppliers bargain with a monopoly intermediary selling products to final consumers. Conventional wisdom holds that such transactions lower negotiated prices when the products are complements for consumers and raise them when they are substitutes. The idea is that consumer demand relationships carry

Rushi Gong, Shun-Li Shang, Yi Wang, Jorge Paz Soldan Palma

The thermodynamic description of the (LiF, NaF, KF, CrF2)-CrF3 systems has been revisited, aiming for a better understanding of the effects of Cr on the FLiNaK molten salt. First-principles calculations based on density functional theory (DFT) were performed to determine the electronic and structural properties of each compound, including the formation entha

Chunyi Li, Xun Lin, Xiaolei Zhao

Let $X$ and $Y$ be two smooth projective varieties such that there is a fully faithful exact functor from $D^b(\mathrm{Coh}(X))$ to $D^b(\mathrm{Coh}(Y))$. We show that $X$ and $Y$ are birational equivalent if the functor maps one skyscraper sheaf to a skyscraper sheaf. Further assuming that $X$ and $Y$ are of the same dimension, we show that if $X$ has ampl

Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh, Kamalika Chaudhuri

Machine learning models are increasingly used in societal applications, yet legal and privacy concerns demand that they very often be kept confidential. Consequently, there is a growing distrust about the fairness properties of these models in the minds of consumers, who are often at the receiving end of model predictions. To this end, we propose \name -- a

Biswajit Khara, Robert Dyja, Kumar Saurabh, Anupam Sharma

We present a space-time continuous-Galerkin finite element method for solving incompressible Navier-Stokes equations. To ensure stability of the discrete variational problem, we apply ideas from the variational multi-scale method. The finite element problem is posed on the ``full" space-time domain, considering time as another dimension. We provide a rigorou

Avinandan Bose, Simon Shaolei Du, Maryam Fazel

We study the problem of representation transfer in offline Reinforcement Learning (RL), where a learner has access to episodic data from a number of source tasks collected a priori, and aims to learn a shared representation to be used in finding a good policy for a target task. Unlike in online RL where the agent interacts with the environment while learning

Elia Zanoni, Carlo Maria Scandolo

Many resource theories share an interesting property: An operation is free if and only if its renormalized Choi matrix is a free state. In this article, we refer to resource theories exhibiting this property as Choi-defined resource theories. We demonstrate how and under what conditions one can construct a Choi-defined resource theory, and we prove that when

Guan Wang, Rebecca Frederick, Jinglong Duan, William Wong

In this paper, we delve into the rapidly evolving challenge of misinformation detection, with a specific focus on the nuanced manipulation of narrative frames - an under-explored area within the AI community. The potential for Generative AI models to generate misleading narratives underscores the urgency of this problem. Drawing from communication and framin

Natasha Tomm, Nadia O. Antoniadis, Marcelo Janovitch, Matteo Brunelli

A quantum emitter interacting with photons in a single optical-mode constitutes a one-dimensional atom. A coherent and efficiently coupled one-dimensional atom provides a large nonlinearity, enabling photonic quantum gates. Achieving a high coupling efficiency ($\beta$-factor) and low dephasing is challenging. Here, we use a semiconductor quantum dot in an o

Jakob Führer, Géza Tóth

Conlon and Wu showed that there is a red/blue-coloring of $\mathbb{E}^n$ that does not contain $3$ red collinear points separated by unit distance and $m=10^{50}$ blue collinear points separated by unit distance. We prove that the statement holds with $m=1177$. We show similar results with different distances between the points.

Kundan Krishna, Sanjana Ramprasad, Prakhar Gupta, Byron C. Wallace

LLMs can generate factually incorrect statements even when provided access to reference documents. Such errors can be dangerous in high-stakes applications (e.g., document-grounded QA for healthcare or finance). We present GenAudit -- a tool intended to assist fact-checking LLM responses for document-grounded tasks. GenAudit suggests edits to the LLM respons

Aymen Khaleel, Recep Vural, Mehmet Cagri Ilter, Majid Gerami

Reconfigurable intelligent surface (RIS)-empowered communication is one of the promising physical layer enabling technologies for the sixth generation (6G) wireless networks due to their unprecedented capabilities in shaping the wireless communication environment. RISs are modeled as passive objects that can not transmit or receive wireless signals. While th

Sandro Roch

Arrangements of pseudolines are a widely studied generalization of line arrangements. They are defined as a finite family of infinite curves in the Euclidean plane, any two of which intersect at exactly one point. One can state various related coloring problems depending on the number $n$ of pseudolines. In this article, we show that $n$ colors are sufficien

Loka Li, Zhenhao Chen, Guangyi Chen, Yixuan Zhang

The recent success of Large Language Models (LLMs) has catalyzed an increasing interest in their self-correction capabilities. This paper presents a comprehensive investigation into the intrinsic self-correction of LLMs, attempting to address the ongoing debate about its feasibility. Our research has identified an important latent factor - the "confidence" o

Shipra Agrawal, Wei Tang

We consider a dynamic pricing problem where customer response to the current price is impacted by the customer price expectation, aka reference price. We study a simple and novel reference price mechanism where reference price is the average of the past prices offered by the seller. As opposed to the more commonly studied exponential smoothing mechanism, in

Carolin Bauerhenne, Rainer Kolisch, Andreas S. Schulz

Appointment scheduling problems under uncertainty encounter a fundamental trade-off between cost minimization and customer waiting times. Most existing studies address this trade-off using a weighted sum approach, which puts little emphasis on individual waiting times and, thus, customer satisfaction. In contrast, we study how to minimize total cost while pr

Aryaman Arora, Dan Jurafsky, Christopher Potts

Language models (LMs) have proven to be powerful tools for psycholinguistic research, but most prior work has focused on purely behavioural measures (e.g., surprisal comparisons). At the same time, research in model interpretability has begun to illuminate the abstract causal mechanisms shaping LM behavior. To help bring these strands of research closer toge

Bogdan Alecu, Mamadou Moustapha Kanté, Vadim Lozin, Viktor Zamaraev

Lettericity is a graph parameter responsible for many attractive structural properties. In particular, graphs of bounded lettericity have bounded linear clique-width and they are well-quasi-ordered by induced subgraphs. The latter property implies that any hereditary class of graphs of bounded lettericity can be described by finitely many forbidden induced s

María Teresa García-Ordás, Natalia Arias, Carmen Benavides, Oscar García-Olalla

COVID-19 disease has affected almost every country in the world. The large number of infected people and the different mortality rates between countries has given rise to many hypotheses about the key points that make the virus so lethal in some places. In this study, the eating habits of 170 countries were evaluated in order to find correlations between the

Michael Gunn, Dohyun Park, Nidhish Kamath

In this study, we investigate the potential of GPT-4 and its advanced iteration, GPT-4 Turbo, in autonomously developing a detailed entity type taxonomy. Our objective is to construct a comprehensive taxonomy, starting from a broad classification of entity types - including objects, time, locations, organizations, events, actions, and subjects - similar to e

Inna Wanyin Lin, Ashish Sharma, Christopher Michael Rytting, Adam S. Miner

Navigating certain communication situations can be challenging due to individuals' lack of skills and the interference of strong emotions. However, effective learning opportunities are rarely accessible. In this work, we conduct a human-centered study that uses language models to simulate bespoke communication training and provide just-in-time feedback to su

Dylan Spicker, Michael P. Wallace, Grace Y. Yi

Dynamic treatment regimes (DTRs) are sequences of functions that formalize the process of precision medicine. DTRs take as input patient information and output treatment recommendations. A major focus of the DTR literature has been on the estimation of optimal DTRs, the sequences of decision rules that result in the best outcome in expectation, across the co

Danna Zheng, Mirella Lapata, Jeff Z. Pan

We present Archer, a challenging bilingual text-to-SQL dataset specific to complex reasoning, including arithmetic, commonsense and hypothetical reasoning. It contains 1,042 English questions and 1,042 Chinese questions, along with 521 unique SQL queries, covering 20 English databases across 20 domains. Notably, this dataset demonstrates a significantly high

Jean Hélder Marques Ribeiro, Kunihiko Taira

We perform direct numerical simulations (DNS) of actively controlled laminar separated wakes around low-aspect-ratio wings with two primary goals: (i) reducing the size of the separation bubble and (ii) attenuating the wing tip vortex. Instead of preventing separation, we modify the three-dimensional ($3$-D) dynamics to exploit wake vortices for aerodynamic

Jacek Jakimiuk, Hermann König

Eskenazis, Nayar and Tkocz have shown recently some resilience of Ball's celebrated cube slicing theorem, namely its analogue in $l^n_p$ for large $p$. We show that the complex analogue, i.e. resilience of the polydisc slicing theorem proven by Oleszkiewicz and Pelczy\'nski, holds for large $p$ and small $n$, but does not hold for any $p > 2$ and large $n$.

Ganesh Sapkota, Sanjay Madria

Localization in a battlefield environment is increasingly challenging as GPS connectivity is often denied or unreliable, and physical deployment of anchor nodes across wireless networks for localization can be difficult in hostile battlefield terrain. Existing range-free localization methods rely on radio-based anchors and their average hop distance which su

James Oldfield, Markos Georgopoulos, Grigorios G. Chrysos, Christos Tzelepis

The Mixture of Experts (MoE) paradigm provides a powerful way to decompose dense layers into smaller, modular computations often more amenable to human interpretation, debugging, and editability. However, a major challenge lies in the computational cost of scaling the number of experts high enough to achieve fine-grained specialization. In this paper, we pro

Rajat Gupta, Noah Lebowitz-Lockard, Joseph Vandehey

A classic theorem of Uchimura states that the difference between the sum of the smallest parts of the partitions of $n$ into an odd number of distinct parts and the corresponding sum for an even number of distinct parts is equal to the number of divisors of $n$. In this article, we initiate the study of the $k$th smallest part of a partition $\pi$ into disti

Abdollah Jalilian, Francisco Cuevas-Pacheco, Ganggang Xu, Rasmus Waagepetersen

The dynamics of a rain forest is extremely complex involving births, deaths and growth of trees with complex interactions between trees, animals, climate, and environment. We consider the patterns of recruits (new trees) and dead trees between rain forest censuses. For a current census we specify regression models for the conditional intensity of recruits an

Nigel P. Byott, Fabio Ferri

We prove a conjecture of Guarnieri and Vendramin on the number of braces of a given order whose multiplicative group is a generalised quaternion group. At the same time, we give a similar result where the multiplicative group is dihedral. We also enumerate Hopf-Galois structures of abelian type on Galois extensions with generalised quaternion or dihedral Gal

Raymond A. Haltli, Eric Ou, Christopher D. Nordquist, Susan M. Clark

Stringent physical requirements need to be met for the high performing surface-electrode ion traps used in quantum computing, sensing, and timekeeping. In particular, these traps must survive a high temperature environment for vacuum chamber preparation and support high voltage rf on closely spaced electrodes. Due to the use of gold wire bonds on aluminum pa

Danna Zheng, Danyang Liu, Mirella Lapata, Jeff Z. Pan

Large Language Models (LLMs) have demonstrated impressive capabilities across various domains, prompting a surge in their practical applications. However, concerns have arisen regarding the trustworthiness of LLMs outputs, particularly in closed-book question-answering tasks, where non-experts may struggle to identify inaccuracies due to the absence of conte

Luisa T. Buchman, Matthew D. Duez, Marlo Morales, Mark A. Scheel

Errors due to imperfect boundary conditions in numerical relativity simulations of binary black holes can produce unphysical reflections of gravitational waves which compromise the accuracy of waveform predictions, especially for subdominant modes. A system of higher order absorbing boundary conditions which greatly reduces this problem was introduced in ear

Marek Hyčko

Using already known resuls concerning the structure of (normal) subgroups of a $U_{6n}$ group we provide a dynamical programming algoritm for counting the number of all (normal) fuzzy subgroups of $U_{6n}$ with respect to M. T\u{a}rn\u{a}ceanu and L. Bentea equivalence relation.

Luke Oeding, Ian Tan

We introduce a broad lemma, one consequence of which is the higher order singular value decomposition (HOSVD) of tensors defined by DeLathauwer, DeMoor and Vandewalle (2000). By an analogous application of the lemma, we find a complex orthogonal version of the HOSVD. Kraus' (2010) algorithm used the HOSVD to compute normal forms of almost all $n$-qubit pure

Yuying Zhao, Yu Wang, Yi Zhang, Pamela Wisniewski

Online dating platforms have gained widespread popularity as a means for individuals to seek potential romantic relationships. While recommender systems have been designed to improve the user experience in dating platforms by providing personalized recommendations, increasing concerns about fairness have encouraged the development of fairness-aware recommend

Ibrahim Ozkan, Atila Yilmaz

Cardiovascular system diseases can be identified by using a specialized diagnostic process utilizing a digital stethoscope. Digital stethoscopes provide phonocardiography (PCG) recordings for further inspection, besides filtering and amplification of heart sounds. In this paper, a framework that is useful to develop feature extraction and classification of P

D. J. Needham, S. Langdon

We develop a model for the interaction of a fluid flowing above an otherwise static particle bed, with generally the particles being entrained or detrained into the fluid from the upper surface of the particle bed, and thereby forming a fully two phase fluidized cloud above the particle bed. The flow in this large scale fluidized region is treated as a two-p

Max Langtry, Vijja Wichitwechkarn, Rebecca Ward, Chaoqun Zhuang

Data is required to develop forecasting models for use in Model Predictive Control (MPC) schemes in building energy systems. However, data is costly to both collect and exploit. Determining cost optimal data usage strategies requires understanding of the forecast accuracy and resulting MPC operational performance it enables. This study investigates the perfo

Abulkarim Faraj Alqahtani, Mohammad Ilyas

The pervasive use of social media platforms, such as Facebook, Instagram, and X, has significantly amplified our electronic interconnectedness. Moreover, these platforms are now easily accessible from any location at any given time. However, the increased popularity of social media has also led to cyberbullying.It is imperative to address the need for findin

Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas Diggavi

Statistical heterogeneity of clients' local data is an important characteristic in federated learning, motivating personalized algorithms tailored to the local data statistics. Though there has been a plethora of algorithms proposed for personalized supervised learning, discovering the structure of local data through personalized unsupervised learning is les

Cédric Picron

Since the emergence of deep learning, the computer vision field has flourished with models improving at a rapid pace on more and more complex tasks. We distinguish three main ways to improve a computer vision model: (1) improving the data aspect by for example training on a large, more diverse dataset, (2) improving the training aspect by for example designi

Siqi Miao, Zhiyuan Lu, Mia Liu, Javier Duarte

This study introduces a novel transformer model optimized for large-scale point cloud processing in scientific domains such as high-energy physics (HEP) and astrophysics. Addressing the limitations of graph neural networks and standard transformers, our model integrates local inductive bias and achieves near-linear complexity with hardware-friendly regular o

William Herbst, James P. Greenwood

Chondrules probably formed during a small window of time $\sim$1-4 Ma after CAIs, when most solid matter in the asteroid belt was already in the form of km-sized planetesimals. They are unlikely, therefore, to be ``building blocks" of planets or abundant on asteroids, but more likely to be a product of energetic events common in the asteroid belt at that epo

Harbir Antil, Madeline O. Horton, Mahamadi Warma

This paper introduces a new class of variational inequalities where the obstacle is placed in the exterior domain that is disjoint from the observation domain. This is carried out with the help of nonlocal fractional operators. The need for such novel variational inequalities stems from the fact that the classical approach only allows placing the obstacle ei

Mateen Ulhaq, Ivan V. Bajić

Due to the limited computational capabilities of edge devices, deep learning inference can be quite expensive. One remedy is to compress and transmit point cloud data over the network for server-side processing. Unfortunately, this approach can be sensitive to network factors, including available bitrate. Luckily, the bitrate requirements can be reduced with

Sagar Saxena, Mohammad Nayeem Teli

Deep generative models have been applied to multiple applications in image-to-image translation. Generative Adversarial Networks and Diffusion Models have presented impressive results, setting new state-of-the-art results on these tasks. Most methods have symmetric setups across the different domains in a dataset. These methods assume that all domains have e

Yanda Chen, Chen Zhao, Zhou Yu, Kathleen McKeown

Pre-trained language models (LMs) are capable of in-context learning (ICL): they can adapt to a task with only a few examples given in the prompt without any parameter update. However, it is unclear where this capability comes from as there is a stark distribution shift between pre-training text and ICL prompts. In this work, we study what patterns of the pr

Alexey Kokotov, Dmitrii Korikov

We study the regularized determinants ${\rm det}\, \Delta$ of various self-adjoint extensions of symmetric Laplacians acting in spinor bundles over compact Riemann surfaces with flat singular metrics $|\omega|^2$, where $\omega$ is a holomorphic one form on the Riemann surface. We find an explicit expression for ${\rm det}\, \Delta$ for the so-called self-ad

Andrzej Daniluk, Evgeny Lakshtanov, Rafal Muchorski

We present a novel technique of Monte Carlo error reduction that finds direct application in option pricing and Greeks estimation. The method is applicable to any LSV modelling framework and concerns a broad class of payoffs, including path-dependent and multi-asset cases. Most importantly, it allows to reduce the Monte Carlo error even by an order of magnit

Anya Sims, Cong Lu, Jakob Foerster, Yee Whye Teh

Offline reinforcement learning aims to train agents from pre-collected datasets. However, this comes with the added challenge of estimating the value of behaviors not covered in the dataset. Model-based methods offer a potential solution by training an approximate dynamics model, which then allows collection of additional synthetic data via rollouts in this

Yasameen Sajid Razooqi, Muntasir Al-Asfoor, Mohammed Hamzah Abed

Routing represents a pivotal concern in the context of Wireless Sensor Networks (WSN) owing to its divergence from traditional network routing paradigms. The inherent dynamism of the WSN environment, coupled with the scarcity of available resources, engenders considerable challenges for industry and academia alike in devising efficient routing strategies. Ad

Truong Thanh Hung Nguyen, Tobias Clement, Phuc Truong Loc Nguyen, Nils Kemmerzell

LangXAI is a framework that integrates Explainable Artificial Intelligence (XAI) with advanced vision models to generate textual explanations for visual recognition tasks. Despite XAI advancements, an understanding gap persists for end-users with limited domain knowledge in artificial intelligence and computer vision. LangXAI addresses this by furnishing tex

Carlos Gómez-Cabello, Pascal Lefèvre, Hervé Queffélec

Since their introduction in 1997, the Hardy spaces of Dirichlet series have been broadly and deeply studied. The increasing interest sparked by these Banach spaces of Dirichlet series motivated the introduction of new such spaces, as the Bergman spaces of Dirichlet series $\mathcal{A}^p_{\mu}$ here considered, where $\mu$ is a probability measure on $(0,\inf

Carlos Gómez-Cabello, Pascal Lefèvre, Hervé Queffélec

The theory of Banach spaces of Dirichlet series has drawn an increasing attention in the recent 25 years. One of the main interest of this new theory is that of defining analogues of the classical spaces of analytic functions on the unit disc. In this sense, Bergman spaces were introduced several years ago contributing to broaden the picture of this theory.

Teng Wu, Bruno Vallet, Marc Pierrot-Deseilligny, Ewelina Rupnik

Dense matching is crucial for 3D scene reconstruction since it enables the recovery of scene 3D geometry from image acquisition. Deep Learning (DL)-based methods have shown effectiveness in the special case of epipolar stereo disparity estimation in the computer vision community. DL-based methods depend heavily on the quality and quantity of training dataset

Biny Sebastian, Anderson Caproni, Preeti Kharb, A. J. Nayana

Identifying methods to discover dual AGN has proven to be challenging. Several indirect tracers have been explored in the literature, including X/S-shaped radio morphologies and double-peaked (DP) emission lines in the optical spectra. However, the detection rates of confirmed dual AGN candidates from the individual methods remain extremely small. We search

Sina Hossein Zadeh, Cem Cakirhan, Danial Khatamsaz, John Broucek

The martensitic transformation in NiTi-based Shape Memory Alloys (SMAs) provides a basis for shape memory effect and superelasticity, thereby enabling applications requiring solid-state actuation and large recoverable shape changes upon mechanical load cycling. In order to tailor the transformation to a particular application, the compositional dependence of

Mai Gamal, Mohamed Rashad, Eman Ehab, Seif Eldawlatly

Extensive literature has drawn comparisons between recordings of biological neurons in the brain and deep neural networks. This comparative analysis aims to advance and interpret deep neural networks and enhance our understanding of biological neural systems. However, previous works did not consider the time aspect and how the encoding of video and dynamics

Wei Zhang, Brian Barr, John Paisley

Deep neural networks have revolutionized many fields, but their black-box nature also occasionally prevents their wider adoption in fields such as healthcare and finance, where interpretable and explainable models are required. The recent development of Neural Additive Models (NAMs) is a significant step in the direction of interpretable deep learning for ta

Cheng Wang, Pengtao Sun, Yumiao Zhang, Jinchao Xu

Based upon two overlapped, body-unfitted meshes, a type of unified-field monolithic fictitious domain-finite element method (UFMFD-FEM) is developed in this paper for moving interface problems of dynamic fluid-structure interactions (FSI) accompanying with high-contrast physical coefficients across the interface and contacting collisions between the structur

Agustin J. Lapi, Miguel Sofo-Haro, Benjamin C. Parpillon, Adi Birman

The Skipper-in-CMOS image sensor integrates the non-destructive readout capability of Skipper Charge Coupled Devices (Skipper-CCDs) with the high conversion gain of a pinned photodiode in a CMOS imaging process, while taking advantage of in-pixel signal processing. This allows both single photon counting as well as high frame rate readout through highly para

Aaradhya Pandey, Sanjeev Kulkarni

In this paper, we study the exact recovery problem in the Gaussian weighted version of the Stochastic block model with two symmetric communities. We provide the information-theoretic threshold in terms of the signal-to-noise ratio (SNR) of the model and prove that when SNR $<1$, no statistical estimator can exactly recover the community structure with probab

Jose Luis Castiglioni, Rodolfo Ertola-Biraben

In [Incer Romeo, I. X., \textit{The Algebra of Contracts}. Ph.D. Thesis, UC Berkeley (2022)] an algebraic perspective on assume-guarantee contracts is proposed. This proposal relies on a construction involving Boolean algebras. However, the structures thus proposed lack a clearly prescribed set of basic operations, necessary if we want to see them as a class

Usama Muneeb, Mesrob I. Ohannessian

We consider scenarios where a very accurate (often small) predictive model using restricted features is available when training a full-featured (often larger) model. This restricted model may be thought of as side-information'', and can come either from an auxiliary dataset or from the same dataset by forcing the restriction. How can the restricted model be

Sven Brüggemann, Dominic Nightingale, Jack Silberman, Maurício de Oliveira

We propose a design method for a robust safety filter based on Input Constrained Control Barrier Functions (ICCBF) for car-like robots moving in complex environments. A robust ICCBF that can be efficiently implemented is obtained by learning a smooth function of the environment using Support Vector Machine regression. The method takes into account steering c

Lazare Osmanov, Khomeriki Ramaz

We investigate regular and chaotic dynamics of Two Bodies Swinging on a Rod, which differs from all the other mechanical analogies: depending on initial conditions, its oscillation could end very quickly and the reason is not a drag force or energy loss. We use various tools to analyze motion, such as Poincar\'e section for quasi-periodic and chaotic cases.

E. M. C. Sijben, J. C. Jansen, P. A. N. Bosman, T. Alderliesten

Paragangliomas are rare, primarily slow-growing tumors for which the underlying growth pattern is unknown. Therefore, determining the best care for a patient is hard. Currently, if no significant tumor growth is observed, treatment is often delayed, as treatment itself is not without risk. However, by doing so, the risk of (irreversible) adverse effects due

Carl Winge, Adam Imdieke, Bahaa Aldeeb, Dongyeop Kang

Training generalist robot agents is an immensely difficult feat due to the requirement to perform a huge range of tasks in many different environments. We propose selectively training robots based on end-user preferences instead. Given a factory model that lets an end user instruct a robot to perform lower-level actions (e.g. 'Move left'), we show that end u