Towards a Theory of Bullshit Visualization

In this unhinged rant, I lay out my suspicion that a lot of visualizationsare bullshit . I suspect that bullshit charts take up a large fraction of the time and attention of actual visualization producers and consumers, and yet are apparently absent from academic research into visualization design .…

Tactile Grasp Refinement using Deep Reinforcement Learning and Analytic Grasp Stability Metrics

A combination of geometric and force-agnostic grasp stability metrics yields the highest average success rates of 95.4% for cuboids, 93.1% for cylinders, and62.3% for spheres across wrist position errors between 0 and 7 centimeters . In a second experiment, we show that grasp refinement algorithms trained with contact feedback (contact positions, normals, and forces) perform up to 6.6% better than a baseline that receives no tactile information .…

Multidimensional Scaling Approximation and Complexity

Metric Multidimensional scaling (MDS) is a classical method for generating meaningful (non-linear) low-dimensional embeddings of high-dimensional data . Despite its ubiquity, our theoreticalunderstanding of MDS remains limited as its objective function is highlynon-convex . In this paper, we prove that minimizing the Kamada-Kawai objectiveis NP-hard and give a provable approximation algorithm for optimizing it, which is a PTAS on low-diameter graphs .…

DeepRare Generic Unsupervised Visual Attention Models

DeepRare2021 (DR21) is an evolution of a previous version called DeepRare2019 (DR19) based on a common framework . DR21 does not need any training and uses thedefault ImageNet training, 2) is fast even on CPU, 3) is tested on four verydifferent eye-tracking datasets showing that the DR21 is generic and is always in the within the top models on all datasets and metrics .…

Multi view Contrastive Self Supervised Learning of Accounting Data Representations for Downstream Audit Tasks

International audit standards require the direct assessment of a financial statement’s underlying accounting transactions, referred to as journal entries . We propose a contrastive self-supervisedlearning framework designed to learn audit task invariant accounting datarepresentations to meet this requirement . The framework encompasses deliberateinteracting data augmentation policies that utilize the attributecharacteristics of journal entry data .…

Models for Narrative Information A Study

The major objective of this work is to study and report the existingontology-driven models for narrative information . The findingsexplicate a comparative view of the narrative models across domains . The findings demonstrate the similarities anddifferences among the elements of the elements in the ontology across domains.…

Remaining useful life prediction with uncertainty quantification development of a highly accurate model for rotating machinery

Rotating machinery is essential to modern life, from power generation totransportation and a host of other industrial applications . accurate remaining useful life (RUL) prediction is essential for maintenance planning and to prevent catastrophic failures . We devise a novelarchitecture and RUL prediction model with uncertainty quantification, termedVisPro, which integrates time-frequency analysis, deep learning imagerecognition, and nonstationary Gaussian process regression .…

Report on the The Future of the Shell Panel at HotOS 2021

This document summarizes the challenges and possible research directions around the shell and its ecosystem, collected during and after the HotOS21Panel on the future of the shell . The goal is to create a snapshot of what anumber of researchers from various disciplines — connected to the shell to varying degrees — think about its future .…

Models for Narrative Information A Study

The major objective of this work is to study and report the existingontology-driven models for narrative information . The findingsexplicate a comparative view of the narrative models across domains . The findings demonstrate the similarities anddifferences among the elements of the elements in the ontology across domains.…

Multi view Contrastive Self Supervised Learning of Accounting Data Representations for Downstream Audit Tasks

International audit standards require the direct assessment of a financial statement’s underlying accounting transactions, referred to as journal entries . We propose a contrastive self-supervisedlearning framework designed to learn audit task invariant accounting datarepresentations to meet this requirement . The framework encompasses deliberateinteracting data augmentation policies that utilize the attributecharacteristics of journal entry data .…

A peridynamics based finite element method for quasi static fracture analysis

A peridynamics-based finite element method (Peri-FEM) is proposed for the quasi-static fracture analysis . The method is of the consistentcomputational framework with the classical finite elements method . The validity of the proposed method is demonstrated through numerical examples . In this paper, the author proposes a peridynamic element (PE) method to analyze quasional fracture analysis of the structure of a structure .…

Remaining useful life prediction with uncertainty quantification development of a highly accurate model for rotating machinery

Rotating machinery is essential to modern life, from power generation totransportation and a host of other industrial applications . accurate remaining useful life (RUL) prediction is essential for maintenance planning and to prevent catastrophic failures . We devise a novelarchitecture and RUL prediction model with uncertainty quantification, termedVisPro, which integrates time-frequency analysis, deep learning imagerecognition, and nonstationary Gaussian process regression .…

A peridynamics based finite element method for quasi static fracture analysis

A peridynamics-based finite element method (Peri-FEM) is proposed for the quasi-static fracture analysis . The method is of the consistentcomputational framework with the classical finite elements method . The validity of the proposed method is demonstrated through numerical examples . In this paper, the author proposes a peridynamic element (PE) method to analyze quasional fracture analysis of the structure of a structure .…

Learning the noise fingerprint of quantum devices

Noise’smain features are expected to strictly depend on the physical platform on which the quantum device is realized, in the form of a distinguishable fingerprint . Noise sources unavoidably affect any quantum technological device . Noise sources are also expected to evolve and change over time .…

A complete and continuous map of the Lattice Isometry Space for all 3 dimensional lattices

A periodic3-dimensional lattice is an infinite set of all integer linear combinations ofbasis vectors in Euclidean 3-space . The resulting spaceLISP consists of infinitely many isometry classes of lattices . In dimension 3,we parameterise this continuous space LISP by six coordinates and introduce newmetrics satisfying the metric axioms and continuity under all perturbations .This…

Can Question Generation Debias Question Answering Models A Case Study on Question Context Lexical Overlap

Question answering (QA) models for reading comprehension exploit unintended dataset biases such as question-contextlexical overlap . This hinders QA models from generalizing to under-representedsamples such as questions with low lexical overlap. To address this problem, we use a synonymreplacement-based approach to augment questions with high lexical overlapping.…

Shaping Large Population Agent Behaviors Through Entropy Regularized Mean Field Games

Mean-field games (MFG) were introduced to efficiently analyze approximateNash equilibria in large population settings . We show that entropy regularization provides thenecessary regularity conditions, that are lacking in the standard finite meanfield games . We establish conditions for the existence of a Nashequilibrium in the limiting case as $N$ tends to infinity, and we demonstratethat the Nash equilibrium for the infinite population case is also an$epsilon$-Nash equilibrium .…

Zero Shot Information Extraction as a Unified Text to Triple Translation

We cast a suite of information extraction tasks into a text-to-tripletranslation framework . Instead of solving each task relying on task-specificdatasets and models, we formalize the task as a translation betweentask-specific input text and output triples . We study the zero-shot performance of this framework on open information extraction(OIE2016, NYT, WEB, PENN), relation classification (FewRel and TACRED), andfactual probe (Google-RE and T-REx) The model transfers non-trivially to most tasks and is often competitive with a fully supervised method without the need for any task- specific training .…

DVC P Deep Video Compression with Perceptual Optimizations

The proposed DVC-P is based on Deep Video Compression (DVC) network, but improves it with perceptual optimization . Adiscriminator network and a mixed loss are employed to help our network tradeoff among distortion, perception and rate . The proposed method can generate videos with higher perceptual quality achieving 12.27% reduction in aperceptual BD-rate equivalent, on average, compared with the baseline DVC, .…

Remaining useful life prediction with uncertainty quantification development of a highly accurate model for rotating machinery

Rotating machinery is essential to modern life, from power generation totransportation and a host of other industrial applications . accurate remaining useful life (RUL) prediction is essential for maintenance planning and to prevent catastrophic failures . We devise a novelarchitecture and RUL prediction model with uncertainty quantification, termedVisPro, which integrates time-frequency analysis, deep learning imagerecognition, and nonstationary Gaussian process regression .…

A peridynamics based finite element method for quasi static fracture analysis

A peridynamics-based finite element method (Peri-FEM) is proposed for the quasi-static fracture analysis . The method is of the consistentcomputational framework with the classical finite elements method . The validity of the proposed method is demonstrated through numerical examples . In this paper, the author proposes a peridynamic element (PE) method to analyze quasional fracture analysis of the structure of a structure .…

Finding a Balanced Degree of Automation for Summary Evaluation

Automatic metrics are cheap and reproducible but sometimes poorly correlated with human judgment . In this work, we proposeflexible semiautomatic to automatic summary evaluation metrics, following thePyramid human evaluation method . Semi-automatic Lite2Pyramid retains thereusable human-labeled Summary Content Units (SCUs) for reference(s) but replaces the manual work of judging SCUs’ presence in system summaries with anatural language inference (NLI) model .…

Temporal Inference with Finite Factored Sets

We propose a new approach to temporal inference inspired by the Pearliancausal inference paradigm . Rather than using directed acyclic graphs, we make use of factoredsets, which are sets expressed as Cartesian products . We show that finitefactored sets are powerful tools for inferring temporal relations .…

Multidimensional Scaling Approximation and Complexity

Metric Multidimensional scaling (MDS) is a classical method for generating meaningful (non-linear) low-dimensional embeddings of high-dimensional data . Despite its ubiquity, our theoreticalunderstanding of MDS remains limited as its objective function is highlynon-convex . In this paper, we prove that minimizing the Kamada-Kawai objectiveis NP-hard and give a provable approximation algorithm for optimizing it, which is a PTAS on low-diameter graphs .…

Union and Intersection of all Justifications

We present new algorithm for computing union and intersection of alljustifications for a given ontological consequence without first computing theset of all justifications . We show that ourapproach works well in practice for expressive DLs . In particular, the union ofall justifications can be computed much faster than with existingjustification-enumeration approaches .…

FooBaR Fault Fooling Backdoor Attack on Neural Network Training

Fault injection attacks are known to be vulnerable to physical attackvectors such as fault injection attacks . As of now, these attacks were only used during the inference phase with the intention to cause amisclassification . In this work, we explore a novel attack paradigm by injecting faults during the training phase of a neural network in a way that the resulting network can be attacked during deployment without the necessity of further faulting .…

Towards a Theory of Bullshit Visualization

In this unhinged rant, I lay out my suspicion that a lot of visualizationsare bullshit . I suspect that bullshit charts take up a large fraction of the time and attention of actual visualization producers and consumers, and yet are apparently absent from academic research into visualization design .…

Active Learning for Argument Strength Estimation

High-quality arguments are an essential part of decision-making . We test uncertainty-basedactive learning (AL) methods on two popular argument-strength data sets . Our extensiveempirical evaluation shows that uncertainty based acquisition functions can not surpass the accuracy reached with the random acquisition on these data sets.…

Multi view Contrastive Self Supervised Learning of Accounting Data Representations for Downstream Audit Tasks

International audit standards require the direct assessment of a financial statement’s underlying accounting transactions, referred to as journal entries . We propose a contrastive self-supervisedlearning framework designed to learn audit task invariant accounting datarepresentations to meet this requirement . The framework encompasses deliberateinteracting data augmentation policies that utilize the attributecharacteristics of journal entry data .…

Filling Crosswords is Very Hard

We revisit a classical crossword filling puzzle which already appeared in Garey\&Jonhson’s book . We show that the problem remains NP-hard even under very severe structural restrictions . The problem becomes FPT, but the parameter dependence isexponential in $n^2$ We show an algorithm with running time $2^{o(n^1)$ would contradict therandomized ETH .…

Filling Crosswords is Very Hard

We revisit a classical crossword filling puzzle which already appeared in Garey\&Jonhson’s book . We show that the problem remains NP-hard even under very severe structural restrictions . The problem becomes FPT, but the parameter dependence isexponential in $n^2$ We show an algorithm with running time $2^{o(n^1)$ would contradict therandomized ETH .…

Joint speaker diarisation and tracking in switching state space model

A state-space model is proposed,where the hidden state expresses the identity of the current active speaker and the predicted locations of all speakers . The model is implemented as a particle filter . Experiments on a Microsoft rich meeting transcription task show that the proposed joint location tracking and diarisation approach is able to perform comparably with other methods that use location information .…

WRENCH A Comprehensive Benchmark for Weak Supervision

Weak Supervision (WS) approaches have had widespread success ineasing the bottleneck of labeling training data for machine learning . But proper measurement and analysis of these approaches remain a challenge . We introduce a benchmark platform, \benchmark, for a thoroughand standardized evaluation of WS approaches .…

Report on the The Future of the Shell Panel at HotOS 2021

This document summarizes the challenges and possible research directions around the shell and its ecosystem, collected during and after the HotOS21Panel on the future of the shell . The goal is to create a snapshot of what anumber of researchers from various disciplines — connected to the shell to varying degrees — think about its future .…

Filling Crosswords is Very Hard

We revisit a classical crossword filling puzzle which already appeared in Garey\&Jonhson’s book . We show that the problem remains NP-hard even under very severe structural restrictions . The problem becomes FPT, but the parameter dependence isexponential in $n^2$ We show an algorithm with running time $2^{o(n^1)$ would contradict therandomized ETH .…

A peridynamics based finite element method for quasi static fracture analysis

A peridynamics-based finite element method (Peri-FEM) is proposed for the quasi-static fracture analysis . The method is of the consistentcomputational framework with the classical finite elements method . The validity of the proposed method is demonstrated through numerical examples . In this paper, the author proposes a peridynamic element (PE) method to analyze quasional fracture analysis of the structure of a structure .…

Evolutionary Clustering of Streaming Trajectories

The widespread deployment of smartphones and location-enabled, networkedin-vehicle devices renders it increasingly feasible to collect streamingtrajectory data of moving objects . The continuous clustering of such data canenable a variety of real-time services, such as identifying representativepaths or common moving trends among objects .…

Orthogonal Graph Neural Networks

Graph neural networks (GNNs) have received tremendous attention due to their superiority in learning node representations . However, stacking more convolutional layers significantly decreases the performance of GNNs . We propose a novel orthogonal featuretransformation, named Ortho-GConv, which could generally augment the existing GNN backbones to stabilize the model training and improve the model’s generalization performance .…

Deep Learning for Ultrasound Beamforming

Diagnostic imaging plays a critical role in healthcare, serving as afundamental asset for timely diagnosis, disease staging and management . Ultrasoundprobes are becoming increasingly compact and portable, with the market demand for low-cost pocket-sized and (in-body) miniaturized devices expanding . There is a strong trend towards 3D imaging and the use of high-frame-rate imaging schemes; both accompanied by dramatically increasing data rates that pose a heavy burden on the probe-system communication and image reconstruction algorithms .…

Scholarly outputs of EU Research Funding Programs Understanding differences between datasets of publications reported by grant holders and OpenAIRE Research Graph in H2020

Linking research results to grants is an essential prerequisite for aneffective monitoring and evaluation of funding programs . OpenAIRE Research Graph offers a complete dataset of scholarly outputs of from EU Research funding programs. We identify possible improvements and make recommendations on how they can be addressed.…