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 .…

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 $k$.…

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 .…

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 .…

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 .…

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 .…

Correlation Sketches for Approximate Join Correlation Queries

In this paper, we introduce a new class of data augmentation queries: join-correlation queries . We propose asketching method that enables the construction of an index for a large number of tables . We also explore different scoring strategies that effectively rank the query results based on how well the columns are correlated with the query .…

Rethinking the Backdoor Attacks Triggers A Frequency Perspective

Backdoor attacks have been considered a severe security threat to deeplearning . Such attacks can make models perform abnormally on inputs with triggers and still retain state-of-the-art performance on cleandata . Many current backdoor attacks exhibit severe high-frequency artifacts, which persistacross different datasets and resolutions .…

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.…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

Hybrid QSS and Dynamic Extended Term Simulation Based on Holomorphic Embedding

Power system simulations that extend over a time period of minutes, hours, oreven longer are called extended-term simulations . Extended-term simulation is needed for many power system analysis tasks (e.g., resilience analysis, renewable energyintegration, cascading failures) The conventional approaches are insufficient for dealing with the extended-time simulation of multi-timescaleprocesses .…

Decentralized Cross Network Identity Management for Blockchain Interoperation

Interoperation for data sharing between permissioned blockchain networksrelies on networks’ abilities to independently authenticate requests andvalidate proofs accompanying the data . This requires counterparty networks to know the identities andcertification chains of each other’s members . But permissioned networks are ad hoc consortia of existing organizations, whose network affiliations may not be well-known or well-established even though their individual identities are .…

Scaling Scaling Laws with Board Games

The performance achievable with a fixed amount of compute degrades predictably as the game gets larger and harder . We further show that the test-time and train-time compute available to an agent can be traded off while maintaining performance . We also show the test time and training time compute available can be trade off while keeping performance on the large scale of the problem .…

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 .…

Active learning using weakly supervised signals for quality inspection

The ability to rapidly updatemachine vision based inspection systems is paramount . We develop amethodology for learning actively, from rapidly mined, weakly (i.e. partially)annotated data, enabling a fast, direct feedback from the operators on theproduction line . We also consider the problem of covariate shift, which arises inevitably due tochanging conditions during data acquisition .…

Prism Private Verifiable Set Computation over Multi Owner Outsourced Databases

Prism is a secret sharing based approach to compute privateset operations (i.e., intersection and union), as well as aggregates overoutsourced databases belonging to multiple owners . Prism enables data owners topre-load the data onto non-colluding servers and exploits the additive and multiplicative properties of secret-shares to compute the above-listedoperations in (at most) two rounds of communication between the servers and the querier .…

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 .…

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 .…

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 .…

Polynomial Circuit Verification using BDDs

Verification is one of the central tasks during circuit design . It is shown that for circuits with specificstructural properties, like e.g. tree-like circuits, and circuits based onmultiplexers derived from BDDs complete formal verification can be carried out in polynomial time and space .…

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 .…

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 .…

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 .…

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 .…

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 .…