Detecting Harmful Memes and Their Targets

Use of Internetmemes has emerged as a powerful means to convey political, psychological, andsocio-cultural opinions . Recent days have witnessed a proliferation of harmful memes targeted to abusevarious social entities . As most harmful memes are highly satirical andabstruse without appropriate contexts, off-the-shelf models may not be adequate to understand their underlying semantics .…

Long Range Feature Propagating for Natural Image Matting

Long-Range Feature Propagating Network (LFPNet) learns the long-rangecontext features outside the reception fields for alpha matte estimation . The proposed method performs favorably against the state-of-the-art methods on theAlphaMatting and Adobe Image Matting datasets . LFPNet is based on deep learning based methods that propagate the alpha values from the known regions to unknown regions according to the similarity between them .…

I heartsuit LA Compilable Markdown for Linear Algebra

I$\heartsuit$LA allows users to write linear algebrain text form and compile the same source into LaTeX, C++/Eigen,Python/NumPy/SciPy, and MATLAB . Inspired by Markdown, a language for writing naturally-structured plain text files thattranslate into valid HTML . We outline the principles of our language design and highlight design decisions that balance readability and precise semantics, and highlight the ability to bridge the gap between readingability and .…

Basil Breaking up BFT with ACID transactions

Basil is the first transactional, leaderless ByzantineFault Tolerant key-value store . Basil leverages ACID transactions to scalably implement the abstraction of a trusted shared log in the presence of Byzantineactors . Basil executes non-conflictingoperations in parallel and commits transactions in a single round-trip duringfault-free executions .…

Merlion A Machine Learning Library for Time Series

Merlion is an open-source machine learning library for timeseries . It features a unified interface for many commonly used models anddatasets for anomaly detection and forecasting . It also provides a uniqueevaluation framework that simulates the live deployment and re-training of amodel in production .…

Closed form solutions for the inverse kinematics of serial robots using conformal geometric algebra

This work addresses the inverse kinematics of serial robots using conformalgeometric algebra . Classical approaches include either the use of homogeneousmatrices, which entails high computational cost and execution time . In this work, we present a compact, elegant andintuitive formulation of robot kinematic based on conformal geometric algebrathat provides a suitable framework for the closed-form resolution of theinverse Kinematic problem for manipulators with a spherical wrist .…

MARMOT A Deep Learning Framework for Constructing Multimodal Representations for Vision and Language Tasks

Political activity on social media presents a data-rich window into political behavior . Almost all content analyses of social media require a data labeling step . Most automated machine classification methods ignore the multimodality of posted content . This paper proposes a novel vision-and-language framework called multimodalrepresentations using modality translation (MARMOT) MARMOT outperforms an ensemble text-onlyclassifier in 19 of 20 categories in multilabel classifications of tweets reporting election incidents during the 2016 U.S.…

Runtime Interchange for Adaptive Re use of Intelligent Cyber Physical System Controllers

Cyber-Physical Systems (CPSs) increasingly adopting Artificial Neural Network (ANN)-based controllers . The verification of such systems is difficult and timeconsuming . These verified controllers are not able to adapt to frequentrequirements changes . This raises the question: How can trained and verified controllers, which have gone through expensive training and verification processes, be re-used to deal with requirement changes?…

Stable Volumes for Persistent Homology

This paper proposes a stable volume and its variant, a stable sub-volume formore reliable data analysis using persistent homology . In a special case, we prove that a stablevolume is the robust part of an optimal volume against noises . This paper also shows some examples of stable volumes andsub-volumes .…

Discrete Hyperbolic Random Graph Model

The hyperbolic random graph model (HRG) has proven useful in the analysis of scale-free networks . However, working with this model is algorithmically and technically challenging because of the nature of the distances in thehyperbolic plane . In this paper, we propose a discrete variant of the HRG modelwhere nodes are mapped to the vertices of a triangulation .…

Runtime Interchange for Adaptive Re use of Intelligent Cyber Physical System Controllers

Cyber-Physical Systems (CPSs) increasingly adopting Artificial Neural Network (ANN)-based controllers . The verification of such systems is difficult and timeconsuming . These verified controllers are not able to adapt to frequentrequirements changes . This raises the question: How can trained and verified controllers, which have gone through expensive training and verification processes, be re-used to deal with requirement changes?…

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 .…

User Defined Functions for HDF5

Scientific datasets are known for their challenging storage demands and the processing pipelines that transform their information . In this paper, we present an infrastructure for the HDF5 file format that enables datasetvalues to be populated on the fly . task-related scripts can be attached intoHDF5 files and only execute when the dataset is read by an application.…

Spatial Information Refinement for Chroma Intra Prediction in Video Coding

Video compression benefits from advanced chroma intra prediction methods, such as the Cross-Component Linear Model (CCLM) Video compression can be improved by refined down-sampling or by incorporating location information . The two proposed methods obtain 0.31%, 2.64%,2.02% and 0.33%, 3.00% BD-rate reduction on Y, Cb and Cr components,respectively, under All-Intra configuration, when implemented in VersatileVideo Coding (H.266/VVC) test model .…

Discrete Hyperbolic Random Graph Model

The hyperbolic random graph model (HRG) has proven useful in the analysis of scale-free networks . However, working with this model is algorithmically and technically challenging because of the nature of the distances in thehyperbolic plane . In this paper, we propose a discrete variant of the HRG modelwhere nodes are mapped to the vertices of a triangulation .…

Stable Volumes for Persistent Homology

This paper proposes a stable volume and its variant, a stable sub-volume formore reliable data analysis using persistent homology . In a special case, we prove that a stablevolume is the robust part of an optimal volume against noises . This paper also shows some examples of stable volumes andsub-volumes .…

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 .…

Discrete Hyperbolic Random Graph Model

The hyperbolic random graph model (HRG) has proven useful in the analysis of scale-free networks . However, working with this model is algorithmically and technically challenging because of the nature of the distances in thehyperbolic plane . In this paper, we propose a discrete variant of the HRG modelwhere nodes are mapped to the vertices of a triangulation .…

Localizing Infinity shaped fishes Sketch guided object localization in the wild

This work investigates the problem of sketch-guided object localization . We propose asketch-conditioned DETR (DEtection TRansformer) architecture which avoids ahard classification and alleviates the domain gap between sketches and imagesto localize object instances . This novel task allows to move towards identifying the objects atpixel level, which is of key importance in several applications .…

Stable Volumes for Persistent Homology

This paper proposes a stable volume and its variant, a stable sub-volume formore reliable data analysis using persistent homology . In a special case, we prove that a stablevolume is the robust part of an optimal volume against noises . This paper also shows some examples of stable volumes andsub-volumes .…

User Defined Functions for HDF5

Scientific datasets are known for their challenging storage demands and the processing pipelines that transform their information . In this paper, we present an infrastructure for the HDF5 file format that enables datasetvalues to be populated on the fly . task-related scripts can be attached intoHDF5 files and only execute when the dataset is read by an application.…

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 .…

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 .…

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 .…

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 .…

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 .…

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, .…