Hardware Oriented Krylov Methods for High Performance Computing

Krylov subspace methods are an essential building block in numerical simulation software . The efficient utilization of modern hardware is a challenge in the development of these methods . Tothis end, we analyze an innovative block Krylovsubspace framework that allowsto balance the computational and data-transfer costs to the hardware .…

Large scale Sustainable Search on Unconventional Computing Hardware

According to one algorithm, PageRank, the worldwide web structure is represented by the Google matrix . Finding such a dominant eigenvector on an ever-growing number of web pages becomes a computationally intensive task incompatible with Moore’s Law . We discuss the feasibility of simulating the PageRank algorithm on large Google matrices using such unconventionalhardware .…

A Review of Formal Methods applied to Machine Learning

We review state-of-the-art formal methods applied to the verification of machine learning systems . Formal methods can providerigorous correctness guarantees on hardware and software systems . Applying formal methods to verify systems that include machinelearning has only been considered recently .…

Backdoor Attack in the Physical World

Backdoor attack intends to inject hidden backdoor into deep neuralnetworks (DNNs) The prediction of infected models will bemaliciously changed if the hidden backdoor is activated by the attacker-defined trigger . Currently, most existing backdoor attacks adopted the setting of static trigger, $i.e.,$…

Hyperloop System Optimization

Hyperloop system design is a uniquely coupled problem because it involves the design of a complex, high-performance vehicle and its accompanying infrastructure . This work presents a system optimization tool, HOPS, that has been adopted as a central component of the Virgin Hyperloop design process .…

Proof Complexity of Symbolic QBF Reasoning

We introduce and investigate symbolic proof systems for Quantified BooleanFormulas (QBF) operating on Ordered Binary Decision Diagrams (OBDDs) Thesesystems capture QBF solvers that perform symbolic quantifier elimination . We obtain exponential separations from standardclausal proof systems, specifically (long-distance) QU-Resolution and IR-Calc .…

Multiscale Governance

Humandemics will propagate because of thepathways that connect the different systems and several invariant behaviors and patterns that have emerged globally . Infodemics ofmisinformation can be a risk as it has occurred in the COVID-19 pandemic . Real-time response systems are thebasis for resilience to be the foundation of robust societies .…

Preferential Structures for Comparative Probabilistic Reasoning

Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical systems for formalizing such reasoning . In the case of reasoning about relative likelihood, a standardqualitative approach using preordered preferential structures yields adramatically different logical system than a quantitative approach usingprobability measures .…

Scene Graph Embeddings Using Relative Similarity Supervision

Scene graphs are a powerful structured representation of the underlying content of images, and embeddings derived from them have been shown to be useful in multiple downstream tasks . In this work, we employ a graphconvolutional network to exploit structure in scene graphs and produce imageembeddings useful for semantic image retrieval .…

Orbit Finite Dimensional Vector Spaces and Weighted Register Automata

We develop a theory of vector spaces spanned by orbit-finite sets . We give a decision procedure for equivalence of weighted registerautomata . The algorithm runs in exponential time, and inpolynomial time for a fixed number of registers . We candecide, with the same complexity, language equivalence for unambiguous registerautomicomata, which improves previous results in three ways: (a) we allow for ordercomparisons on atoms, and not just equality; (b) the complexity isexponentially better .…

Visual Alignment Constraint for Continuous Sign Language Recognition

Vision-based Continuous Sign Language Recognition (CSLR) aims to recognizeunsegmented gestures from image sequences . To solve this problem, we propose a Visual Alignment Constraint (VAC) to enhance the feature extractor with more alignment supervision . The proposed VAC achieves competitive performance on two challenging CSLR datasets and experimental results show its effectiveness .…

Global Software Engineering in the Age of GitHub and Zoom

Much has changed since the inaugural ICGSE conference in 2006 . Tools have improved and awareness of cultural differences is widespread . But the pervasive and profound impact of software inthe world — especially for societal scale systems such as social media –forces new and deeply challenging responsibilities on both developers andademics .…

Growing the Simulation Ecosystem

This research represents an attempt to ignite the growth of a crowd sourced simulation ecosystem of reusable subcomponents for Agent-Based Models . Due to the inherent complexity of simulations, developing this ecosystem will be moredifficult than other knowledge sharing ecosystems, such as machine learning libraries .…

CodeTrans Towards Cracking the Language of Silicone s Code Through Self Supervised Deep Learning and High Performance Computing

CodeTrans is an encoder-decoder transformer model for tasks in the software engineering domain . CodeTrans outperforms the state-of-the-art models on all the tasks . These breakthroughs point out apromising direction for process source code and crack software engineering tasks . To expeditefuture works in thesoftware engineering domain, we have published ourpre-trained models of CodeTrans.…

Young Flattenings in the Schur module basis

There are several isomorphic constructions for the irreducible polynomialrepresentations of the general linear group in characteristic zero . The twomost well-known versions are called Schur modules and Weyl modules . Steven Samused a Weyl module implementation in 2009 for his Macaulay2 package PieriMaps .…

RFQuack A Universal Hardware Software Toolkit for Wireless Protocol Security Analysis and Research

RFquack is an open-source tool and library firmware that combinesthe flexibility of a software-based approach with the determinism and performance of embedded RF frontends . It has an IPython shell and 9 firmware modules for: spectrum scanning, automatic carrier detection and bitrate estimation, in-flight packet filtering andmanipulation, MouseJack, and RollJam (as examples).…

Federated Learning Meets Blockchain in Edge Computing Opportunities and Challenges

Mobile edge computing (MEC) has been envisioned as a promising paradigm to handle the massive volume of data generated from ubiquitous mobile devices forenabling intelligent services with the help of artificial intelligence (AI) The integration of FL and blockchain leads to a new paradigm, called FLchain, which potentially transforms intelligent MEC networks intodecentralized, secure, and privacy-enhancing systems .…

Nonlinear Repair Schemes of Reed Solomon Codes

The problem of repairing linear codes and, in particular, Reed Solomon (RS)codes has attracted a lot of attention in recent years . In this problem, a failed codesymbol (node) needs to be repaired by downloading as little information as possible from a subset of the remaining nodes .…

Deep Learning Based Autonomous Driving Systems A Survey of Attacks and Defenses

The rapid development of artificial intelligence, especially deep learning technology, has advanced autonomous driving systems . However, the safety and security of deep learning-based autonomousdriving are severely challenged by these attacks . This survey provides a thorough analysis of different attacksthat may jeopardize ADSs, as well as the corresponding state-of-the-art defensemechanisms .…

Perceptual Indistinguishability Net PI Net Facial Image Obfuscation with Manipulable Semantics

PI-Net is a privacy-preserving mechanism that achieves image obfuscation with PI guarantee . PI-net achieves significantly better privacy utility trade-off through public imagedata, says study . We propose a formal privacy notion for images, with the consideration of the perceptual similarity, we proposeperceptual indistinguishability (PI) We also propose PI-NET, a privacy protection mechanism that protects images from public data, as well as the privacy-utility trade-offs associated with the privacy of the image .…

Jekyll Attacking Medical Image Diagnostics using Deep Generative Models

Jekyll is a neural styletransfer framework that takes as input a biomedical image of a patient andtranslates it to a new image that indicates an attacker-chosen disease condition . The potential for fraudulent claims based on such generated ‘fake’medical images is significant, and we demonstrate successful attacks on bothX-rays and retinal fundus image modalities.…

GSECnet Ground Segmentation of Point Clouds for Edge Computing

Ground segmentation of point clouds remains challenging because of the sparseand unordered data structure . This paper proposes the GSECnet – GroundSegmentation network for Edge Computing . It is designed to be deployable on a low-poweredge computing unit . Remarkably, our framework achieves the inference runtime of 135.2Hz on a desktop platform.…

Explainability aided Domain Generalization for Image Classification

Traditionally, for most machine learning settings, gaining some degree ofexplainability that tries to give users more insights into how and why thenetwork arrives at its predictions, restricts the underlying model and hinders performance to a certain degree . For example, decision trees are thought of asbeing more explainable than deep neural networks but they lack performance on visual tasks .…

Procrustean Training for Imbalanced Deep Learning

A neural network tends to firstunder-fit the minor classes by classifying most of their data into the major classes in early training epochs . We argue that such an under-fitting phase over-emphasizes the competition between major and minor classes, hindersthe neural network from learning the discriminative knowledge that can be begeneralized to test data .…

3D Human Body Reshaping with Anthropometric Modeling

Reshaping accurate and realistic 3D human bodies poses a fundamental challenge forperson identification, online shopping and virtual reality . Existing approaches often suffer from complex measurement by rangecameras or high-end scanners, which either involve heavy expense cost or resultin low quality .…