Optimizing the hybrid parallelization of BHAC

We present our experience with the modernization on the GR-MHD code BHAC,aimed at improving its novel hybrid (MPI+OpenMP) parallelization scheme . We showcase the use of performance profiling tools usable on x86(Intel-based) architectures . Our performance characterization and threadinganalysis provided guidance in improving the concurrency and thus the efficiencyof the OpenMP parallel regions .…

The Devil is in the Detail Simple Tricks Improve Systematic Generalization of Transformers

Recently, many datasets have been proposed to test the systematicgeneralization ability of neural networks . The companion baseline Transformers, typically trained with default hyper-parameters from standard tasks, are shownto fail dramatically . Here we demonstrate that by revisiting modelconfigurations as basic as scaling of embeddings, early stopping, relativepositional embedding, and Universal Transformer variants, we can drasticallyimprove the performance of Transformers on systematic generalization .…

Quantum Sub Gaussian Mean Estimator

We present a new quantum algorithm for estimating the mean of a real-valued random variable obtained as the output of a quantum computation . Our estimatorachieves a nearly-optimal quadratic speedup over the number of classical i.i.d.samples needed . We obtain new quantum algorithms for the .…

Targeting Underrepresented Populations in Precision Medicine A Federated Transfer Learning Approach

The limited representation of minorities and disadvantaged populations in large-scale clinical and genomics research has become a barrier to translating precision medicine research into practice . Risk prediction models are often found to be underperformed inthese underrepresented populations . In this paper, we propose a two-way data integration strategy that integrates heterogeneous data from diverse populations and from multiple healthcare institutions via a federated transfer learning approach .…

Rule based Adaptations to Control Cybersickness in Social Virtual Reality Learning Environments

Social virtual reality learning environments (VRLEs) provide immersiveexperience to users with increased accessibility to remote learning . Lack of high-performance and secured data delivery in critical VRLE domains (e.g., military training, manufacturing) can disrupt application functionality and induce cybersickness . In the event of an anomaly, the framework features rule-based adaptationsthat are triggered by using various decision metrics .…

GLocal K Global and Local Kernels for Recommender Systems

Recommender systems typically operate on high-dimensional sparse user-item matrix matrix . We propose a Global-Local Kernel-based matrix completionframework, named GLocal-K . Our model outperforms the state-of-the-artbaselines on three collaborative filtering benchmarks: ML-100K, ML-1M, andDouban. We apply our model under the extreme low-resource setting, which includes only a user item rating matrix, with no side information, to an extreme low resource setting .…

Robustness Disparities in Commercial Face Detection

Facial detection and analysis systems have been deployed by large companies and critiqued by scholars and activists for the past decade . We present the first of its kind detailedbenchmark of the robustness of three such systems: Amazon Rekognition,Microsoft Azure, and Google Cloud Platform .…

Learning to Give Checkable Answers with Prover Verifier Games

Prover-Verifier Games (PVGs) is a game-theoretic framework to encourage learningagents to solve decision problems in a verifiable manner . The PVG consists of two learners with competing objectives: a trusted verifier network tries tochoose the correct answer, and a more powerful but untrusted prover network attempts to persuade the verifier of a particular answer .…

COVID 19 reproduction number estimated from SEIR model association with people s mobility in 2020

This paper is an exploratory study of two epidemiological questions on aworldwide basis . How fast is the disease spreading? Are the restrictions(especially mobility restrictions) for people bring the expected effect? To answer the first question, we propose a tool for estimating the reproductionnumber of epidemic (the number of secondary infections $R_t$) based on the SEIR model .…

Machine Learning for Performance Prediction of Spark Cloud Applications

Machine Learning (ML) provides black box solutions to model relationship between application performance and system configuration without requiring in-detail knowledge of the system . We investigate the cost-benefits of using supervised ML models for predicting the performance of applications on Spark, one of today’s most widely used frameworks for big data analysis .…

Representation and Processing of Instantaneous and Durative Temporal Phenomena

In this paper, we propose a new logic based temporal phenomenadefinition language specifically tailored for Complex Event Processing . We demonstrate the expressiveness ofour proposed language by employing a maritime use case where we define maritimeevents of interest . Finally, we analyse the execution semantics of our proposed language for stream processing and introduce the `Phenesthe’ implementationprototype.…

FAST PCA A Fast and Exact Algorithm for Distributed Principal Component Analysis

Principal Component Analysis (PCA) is a fundamental data preprocessing tool in machine learning . The purpose of PCA is two-fold: dimension reduction and feature learning . This paper proposes a distributed PCA algorithm calledFAST-PCA (Fast and exAct diSTributed PCA) The proposed algorithm is efficientin terms of communication and can be proved to converge linearly and exactly to the principal components that lead to dimension reduction as well as uncorrelated features .…

Visual and Language Navigation A Survey and Taxonomy

Visual-and-Language Navigation is a multi-disciplinary field of increasing importance and with extraordinary practicality . This taxonomy enables researchers to better grasp the keypoint of a specific task and identify directions for future research . For multi-turn tasks, we divided them into imperative task and interactive task based on whether the agent responsesto the instructions .…

Distinct Angle Problems and Variants

The Erd\H{o}s distinct distance problem is a ubiquitous problem in discrete geometry . We provide upper and lower bounds on a broad class of distinct angle problems . We introduce a new class of asymptotically optimal point configurations with no four cocircular points .…

Supercomputing Enabled Deployable Analytics for Disaster Response

MIT SuperCloud precompute range of analytics as files that can be used with standard preinstalled software that does not require network access or additional software . In response to the COVID-19 pandemic, this approach was tested for providing geo-spatial census data to allow quick analysis of demographic data for better responding to emergencies .…

Enhancing Model Assessment in Vision based Interactive Machine Teaching through Real time Saliency Map Visualization

Interactive Machine Teaching systems allow users to create customized machinelearning models through an iterative process of user-guided training and modelassessment . They primarily offer confidence scores of each label or class as feedback for assessment by users . However, such feedback doesn’t necessarily suffice for users to confirm the behavior of the model .…

Supercomputing Enabled Deployable Analytics for Disaster Response

MIT SuperCloud precompute range of analytics as files that can be used with standard preinstalled software that does not require network access or additional software . In response to the COVID-19 pandemic, this approach was tested for providing geo-spatial census data to allow quick analysis of demographic data for better responding to emergencies .…

Look It s a Computer Program It s an Algorithm It s AI Does Terminology Affect Human Perceptions and Evaluations of Intelligent Systems

In the media, in policy-making, but also in research articles, intelligentsystems are referred to as algorithms, artificial intelligence, and computerprograms . We hypothesize that such terminologicaldifferences can affect people’s perceptions of properties of intelligent systems . Our findings highlight the need to be mindful when choosing terms to describe intelligent systems,because terminology can have unintended consequences, and may impact therobustness and replicability of HCI research .…

Dynamic Structural Clustering on Graphs

Structural Clustering ($DynClu$) is one of the most popular graph clusteringadigms . The goal is to maintain certain information under updates, so that the result can be retrieved in $O(|V| + |E|) time,upon request . The state-of-the-art worst-case cost for each update, $DynELM$ achieves $O(\log^2 |V|) + \log\frac{M}{\delta^*)$ is the amortized cost for every update, at all times in linear space .…

Security and privacy for 6G A survey on prospective technologies and challenges

Sixth-generation (6G) mobile networks will have to cope with diverse threatson a space-air-ground integrated network environment, novel technologies, and an accessible user information explosion . For now, security and privacy issues for 6G remain largely in concept . Physical layer protection, deep networkslicing, quantum-safe communications, artificial intelligence (AI) security, real-time adaptive security, and novel dataprotection mechanisms such as distributed ledgers and differential privacy are the top promising techniques to mitigate the attack magnitude and personal databreaches substantially .…

Human operator cognitive availability aware Mixed Initiative control

This paper presents a Cognitive Availability Aware Mixed-Initiative Controller for remotely operated mobile robots . The controller enables dynamicswitching between different levels of autonomy (LOA) initiated by either theAI or the human operator . Thisconstitutes a qualitative advancement over previous MI (MI)controllers) The controller is evaluated in a disaster response experiment, in which human operators have to conduct an exploration task with a remote robot.…

Optimal area visibility representations of outer 1 plane graphs

This paper studies optimal-area visibility representations of $n$-vertexouter-1-plane graphs . It claims that any graph of this family admits an embedding-preserving visibilityrepresentation whose area is $O(n^{1.5) The paper claims that this area bound is worst-case optimal . We also extend the study to other representation models and, among other results, constructasymptotically optimal $o(n\, pw(G),$ is the pathwidth of the outer-1 planar graph $G$ The paper concludes that the optimal area bound can be achieved if we do not respect the embedding but still have at most one crossing per edge .…

Approximation algorithms for the random field Ising model

Approximating the partition function of the ferromagnetic Ising model with general external fields is known to be #BIS-hard in the worst case, even forbounded-degree graphs . We establish the existence of fully polynomial-time approximation schemes and samplers with high probability over the random fieldsif the external fields are IID Gaussians with variance larger than a constant .…

Cross domain Single channel Speech Enhancement Model with Bi projection Fusion Module for Noise robust ASR

In recent decades, studies have suggested that phase information is crucial for speech enhancement (SE) We put forward a novel cross-domainspeech enhancement model and a bi-projection fusion (BPF) mechanism fornoise-robust ASR . To evaluate the effectiveness of our proposed method, we conduct an extensive set of experiments on the publicly-available Aishell-1Mandarin benchmark speech corpus .…

Truly Perfect Samplers for Data Streams and Sliding Windows

In the data stream model, $f$ is defined implicitly by asequence of updates to its coordinates, and the goal is to design such asampler in small space . Jayaram and Woodruff (FOCS 2018) gave the first perfect$L_p$ samplers in turnstile streams, using $G(x) space for $p\in(0,2) However, to date all known samplingalgorithms are not truly perfect, since their output distribution is onlypoint-wise $\gamma = 1/\text{poly}(n)$ close to the true distribution .…