HumAID Human Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks

Social networks are widely used for information consumption anddissemination, especially during time-critical events such as natural disasters . Despite its significantly large volume, social media content is often too noisy for direct use in any application . In this paper, we present a new large-scale dataset with~77K human-labeled tweets, sampled from a pool of ~24 million tweets across 19disaster events that happened between 2016 and 2019 .…

Exploring Task Placement for Edge to Cloud Applications using Emulation

A vast and growing number of IoT applications connect physical devices, suchas scientific instruments, technical equipment, machines, and cameras, across heterogeneous infrastructure from the edge to the cloud . As edge and cloud layers are increasingly tightly integrated, imbalancedresource allocations and sub-optimally placed tasks can quickly deteriorate the overall system performance .…

Plinius Secure and Persistent Machine Learning Model Training

Persistent memory (PM) is resilient to power loss, provides fast and fine-granular access to memory (unlike disk storage) and has latency and bandwidth close to DRAM (in the order of ns andGB/s) We present PLINIUS, a ML framework using Intel SGXenclaves for secure training of ML models and PM for fault toleranceguarantees .…

DyGCN Dynamic Graph Embedding with Graph Convolutional Network

Dynamic GraphConvolutional Network (DyGCN) generalizes the embedding propagation scheme of GCN to dynamicsetting in an efficient manner . The most affected nodes are first updated, and then their changes are propagated to the further nodes and leads to theirupdate . Extensive experiments conducted on various dynamic graphs demonstratethat our model can update the node embeddings in a time-saving andperformance-preserving way .…

NeuMIP Multi Resolution Neural Materials

NeuMIP is a neural method for representing and rendering a variety of material appearances at different scales . Classical prefiltering(mipmapping) methods fail to generalize to normals, self-shadowing, fibers or more complex microstructures . We also introduce neural offsets, a novel method which allows rendering materials with intricate parallax effects without anytessellation .…

DRL Assisted Resource Allocation for NOMA MEC Offloading with Hybrid SIC

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) have been regarded as promising technologies to improve computation capability and offloading efficiency of the sixth generation (6G) mobile system . This paper mainly focuses on the hybrid NOMA-MEC system, where multiple users are first grouped into pairs, and users in each pair offload their tasks simultaneously .…

Edsger W Dijkstra a Commemoration

This article is a multiauthored portrait of Edsger Wybe Dijkstra that includes testimonials written by friends, colleagues and students . It provides unique insights into his personality, working style andhabits .…

ELO System for Skat and Other Games of Chance

The ELO ranking system has proven to be a reliable method for calculating therelative skill levels of players in zero-sum games . The evaluation of player strength in trick-taking card games like Skat orBridge is not obvious . We propose a new ELO system for Skat to overcome these weaknesses, based on a tournament scoringsystem .…

Evaluating the state of the art in mapping research spaces a Brazilian case study

Scientific knowledge cannot be seen as a set of isolated fields, but as ahighly connected network . Understanding how research areas are connected is ofparamount importance for adequately allocating funding and human resources . Relationshipbetween disciplines can be drawn from data on data on the trajectory of individualscientists, as researchers often make contributions in a small set of interrelated areas .…

A Cycle Joining Construction of the Prefer Max De Bruijn Sequence

We propose a novel construction for the well-known prefer-max De Bruijnsequence . We show that the construction implies known results from the literature in a straightforward manner . It also forms analternative proof for the seminal FKM-theorem . We also show that it implies the correctness of onion-theoracle onion theorem and of the shift rules for preferred-max and prefer-min .…

LI Net Large Pose Identity Preserving Face Reenactment Network

LI-Net is a large-pose Identity-preserving face reenactment network . The Landmark Transformer is adopted to adjust driving landmark images, which narrows the identity gap between driving and source landmark images . Then the Face Rotation Module and the Expression Enhancing Generator decouple the transformed landmark image into pose and expression features, and re-enact those attributes separately to generate identity-preserved faces with accurate expressions and poses .…

On device Federated Learning with Flower

Federated Learning (FL) allows edge devices to collaboratively learn a shared prediction model while keeping their training data on the device . We present an exploration of on-device FL on various smartphones andembedded devices using the Flower framework . We also evaluate the system cost and discuss how this quantification could be used to design more efficient FL algorithms .…

Minimax Estimation of Linear Functions of Eigenvectors in the Face of Small Eigen Gaps

Eigen vector perturbation analysis plays a vital role in various statistical data science applications . The proposed estimators are nearly minimax optimaleven when the associated eigen-gap is substantially smaller than what is required in prior theory . In order to mitigate a non-negligible bias issue inherent to thenatural “plug-in” estimator, we develop de-biased estimators that (1) achieveminimax lower bounds for a family of scenarios (modulo some logarithmicfactor) and (2) can be computed in a data-driven manner without samplesplitting.…

Optimal Resource Allocation Design for Large IRS Assisted SWIPT Systems A Scalable Optimization Framework

In this paper, we study the optimal resource allocation algorithm design for large intelligent reflecting surface (IRS)-assisted simultaneous wirelessinformation and power transfer (SWIPT) systems . We aim tominimize the total base station (BS) transmit power by jointly optimizing the beamforming and the transmission mode selection policy taking into account the quality-of-service requirements of information decoding and non-linear energyharvesting receivers .…

Destroying Multicolored Paths and Cycles in Edge Colored Graphs

We study the computational complexity of $c$-Colored $P_\ell$ Deletion and $c$. Deletions . We show that both problems are fixed-parameter tractable with respect to the colored neighborhood diversity of the input graph . We also provide hardness results to outline the limits ofparameterization by the standard parameter solution size $k$.…

AI in Smart Cities Challenges and approaches to enable road vehicle automation and smart traffic control

Smart Cities and Communities (SCC) constitute a new paradigm in urbandevelopment . SCC ideates on a data-centered society aiming at improving efficiency by automating and optimizing activities and utilities . Thispaper describes AI perspectives in SCC and gives an overview of AI-basedtechnologies used in traffic to enable road vehicle automation and smarttraffic control .…

Synthesized Trust Learning from Limited Human Feedback for Human Load Reduced Multi Robot Deployments

Human multi-robot system (MRS) collaboration is demonstrating potentials in wide application scenarios . A novel Synthesized Trust Learning (STL) method was developed to model human trust in the collaboration . STL explores two aspects of human trust (trust level and trust preference) and accelerates convergence speed by integrating active learning to reduce workload .…

Strumming to the Beat Audio Conditioned Contrastive Video Textures

We introduce a non-parametric approach for infinite video texture synthesis using a representation learned via contrastive learning . We learnrepresentations for video frames and frame-to-frame transition probabilities byfitting a video-specific model . Tosynthesize a texture, we randomly sample frames with high transitionprobabilities to generate diverse temporally smooth videos with novel sequencesand transitions .…

Semi Supervised Classification of Social Media Posts Identifying Sex Industry Posts to Enable Better Support for Those Experiencing Sex Trafficking

Social media is both helpful and harmful to the work against sex trafficking . The thesis explores the use of semi-supervised classification to identify social media posts that are part of the sex industry . AI and Machine Learning (ML) have been used in work against sextrafficking, but they predominantly focus on detecting Child Sexual Abuse Material .…

Community Detection with Contextual Multilayer Networks

In this paper, we study community detection when we observe $m$ sparsenetworks and a high dimensional covariate matrix, all encoding the same community structure among $n$ subjects . In the asymptotic regime where thenumber of features and the number of subjects $p$ grows proportionally, we find a sharp threshold of phase transition .…

Serverless Predictions 2021 2030

Advances on resource disaggregation will enable transparency for most Cloud applications . ServerlessSuperComputer or Infinite Laptop proposals will be equivalent to Tim Wagner’s serverless supercomputer proposals . We present five serverless predictions for the next decade that will realize this vision of transparency .…

A matrix math facility for Power ISA TM processors

Power ISA(TM) Version 3.1 has introduced a new family of matrix mathinstructions, collectively known as the Matrix-Multiply Assist (MMA) facility . These instructions have led to a power- and area-efficient implementation of ahigh throughput math engine in the future POWER10 processor .…

Pilot Edge Distributed Resource Management Along the Edge to Cloud Continuum

We proposePilot-Edge as a common abstraction for resource management across the edge-to-cloud continuum . Pilot-Edge is based on the pilot abstraction, which provides aFunction-as-a-Service (FaaS) interface for application-level tasks . Theabstraction allows applications to encapsulate common functions in high-leveltasks that can then be configured and deployed across the continuum .…

Maximal and minimal dynamic Petri net slicing

Presenting two new Petri net slicing algorithms to isolate those places and transitions that may contribute tokens to one or more places given (the slicing criterion) The completeness of thefirst algorithm and the minimality of the second algorithm are formally proven .…

PrivGenDB Efficient and privacy preserving query executions over encrypted SNP Phenotype database

PrivGenDB is the first SSE-based approach ensuring the confidentiality of shared SingleNucleotide Polymorphism (SNP)-phenotype data through encryption . It supports a variety of query types on genomic data, including countqueries, Boolean queries, and k’-out-of-k match queries . Computer evaluations on a dataset with 5,000 records and 1,000 SNPs demonstrate that a count/Boolean query and a k-out-to-match query over 40 SNPs take approximately 4.3s and 86.4{\mu}s, respectively, that outperforms the existing schemes .…

Accurate and Efficient Suffix Tree Based Privacy Preserving String Matching

The task of calculating similarities between strings held by different organizations without revealing these strings is an increasingly important problem in areas such as health informatics, national censuses, genomics, and fraud detection . We incorporate a hashing basedencoding technique upon the encoded suffixes to improve privacy againstfrequency attacks such as those exploiting Benford’s law .…

Ethical User Interfaces Exploring the Effects of Dark Patterns on Facebook

Using anempirical design analysis, we identify interface interferences impacting users’ online privacy . We find usage behaviour changes due to increased privacy concerns and report individual cases of addiction and mental health issues . These observations are the results of arapidly changing SNS creating a gap of understanding between users’ interactions with the platform and future consequences .…

Multimodal Entity Linking for Tweets

In many information extraction applications, entity linking (EL) has emerged as a crucial task that allows leveraging information about named entities from a knowledge base . In this paper, we address the task of multimodal entitylinking (MEL), an emerging research field in which textual and visualinformation is used to map an ambiguous mention to an entity in a knowledgebase .…

Valued rank metric codes

In this paper, we study linear spaces of matrices defined over discretelyvalued fields . We take first steps into the theory ofrank-metric codes over discrete valuation rings by means of skew algebras derived from Galois extensions of rings . We modelprojectivizations of rank-metic codes via Mustafin varieties, which we then give sufficient conditions for a decrease in the dimension .…