Adaptively Weighted Top N Recommendation for Organ Matching

Organ matching decision is the most critical decision to assign limited viable organs to the most suitable patients . Currently, organ matching decisions were only made by matching scores calculated viascoring models . AWTR improves performance of the current scoring models by using limited actual matching performance in historical data set as well as thecollected covariates from organ donors and patients .…

SurfaceNet Adversarial SVBRDF Estimation from a Single Image

In this paper we present SurfaceNet, an approach for estimatingspatially-varying bidirectional reflectance distribution function (SVBRDF)material properties from a single image . We pose the problem as an imagetranslation task and propose a novel patch-based generative adversarial network that is able to produce high-quality, high-resolution surface reflectancemaps .…

Lower Bounds for Symmetric Circuits for the Determinant

Dawar and Wilsenach (ICALP 2020) show an exponential separation between the sizes of symmetric arithmeticcircuits for computing the determinant and the permanent . The symmetryrestriction is that the circuits which take a matrix input are unchanged by a permutation applied simultaneously to the rows and columns of the matrix .…

HURRA Human readable router anomaly detection

This paper presents HURRA, a system that aims to reduce the time spent by network operators in the process of network troubleshooting . It consists of two modules that are plugged after any anomaly detection algorithm . The main difficulty in live deployment concerns the automated selection of the algorithm and tuning of its hyper-parameters .…

The decomposition of the higher order homology embedding constructed from the k Laplacian

Understanding the structure of the homology embedding can disclose geometric or topological information from the data . The proposed framework is applied to the problem known to be NP-hard in general . Our spectralloop detection algorithm scales better than existing methods and is effective on diverse data such as point clouds and images .…

ArchaeoDAL A Data Lake for Archaeological Data Management and Analytics

Archaeological data have many different formats (images,texts, sensor data) and can be structured, semi-structured and unstructured . Such variety makes data difficult to collect, store, manage, search and analyze . We propose a generic, flexible andcomplete data lake architecture . Our metadata management system exploitsgoldMEDAL, which is the most complete metadata model currently available .…

SNAC An Unbiased Metric Evaluating Topology Recognize Ability of Network Alignment

Network alignment is a problem of finding the node mapping between similarnetworks . The critical difference between network alignment and exact graph matching is that the network alignment considers node mapping in non-isomorphic graphs with error tolerance . We propose an unbiased metric for network alignment that takesindistinguishable nodes into consideration to address this problem .…

The geometry of non additive stabiliser codes

We present a geometric framework for constructing additive and non-additivestabiliser codes . This framework encompasses stabiliser codes and graphical non-adviser codes .…

When a crisis strikes Emotion analysis and detection during COVID 19

Understanding emotions that people express during large-scale crises helps inform policy makers and first responders about theemotional states of the population . We present CovidEmo, ~1K tweets labeled withemotions. We examine how well large pre-trained language models generalizeacross domains and crises in the task of perceived emotion prediction .…

On Boolean Functions with Low Polynomial Degree and Higher Order Sensitivity

In this paper, we connect the tools from cryptology and complexity theory in the domain of Boolean functions with low polynomial degree and high sensitivity . We show that one can implement resilientBoolean functions on a large number of variables with linear size andlogarithmic depth .…

Reconfigurable Intelligent Surfaces Aided Communication Capacity and Performance Analysis Over Rician Fading Channel

In this work, we consider a single input single output (SISO) system forReconfigurable Intelligent Surface (RIS) assisted mmWave communication . Weconsider Rician channel models over user node to RIS and RIS to Access Point(AP) We obtain closed form expressions for capacity with channel stateinformation (CSI) and without CSI at the transmitter .…

Highly Available Queue oriented Speculative Transaction Processing

QR-Store can achieve a throughput of 1.9 million transactions per second in under 200 milliseconds and a replication head of 8%-25% compared to non-replicated configurations . The paper proposes a generic framework to model the replication process in deterministic transaction processingsystems and use it to study three cases .…

Language instruction plays an essential role in the natural language groundednavigation tasks . We propose a DynamicReinforced Instruction Attacker (DR-Attacker) which learns to mislead thenavigator to move to the wrong target by destroying the most instructive information in instructions at different timesteps .…

Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series

Irregularly sampled time series commonly occur in several domains where they present a significant challenge to standard deep learning models . HeTVAE includes a novel input layer to encode information about input observation sparsity, a temporal VAE architecture topropagate uncertainty due to input sparsity .…

Resource Efficient Mountainous Skyline Extraction using Shallow Learning

Skyline plays a pivotal role in mountainous visual geo-localization and localization/navigation of planetary rovers/UAVs and virtual/augmented realityapplications . We present a novel mountainous skyline detection approach wherewe adapt a shallow learning approach to learn a set of filters to discriminate between edges belonging to sky-mountain boundary and others coming from different regions .…

Type based Enforcement of Infinitary Trace Properties for Java

A common approach to improve software quality is to use programming guidelines to avoid common kinds of errors . In this paper, we consider theproblem of enforcing guidelines for Featherweight Java (FJ) We formalize guidelines as sets of finite or infinite execution traces and develop aregion-based type and effect system for FJ that can enforce such guidelines .…

Error Estimates for Neural Network Solutions of Partial Differential Equations

We develop an error estimator for neural network approximations of PDEs . The proposed approach is based on dual weighted residual estimator (DWR) It isdestined to serve as a stopping criterion that guarantees the accuracy of the solution independently of the design of the neural network training .…

Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series

Irregularly sampled time series commonly occur in several domains where they present a significant challenge to standard deep learning models . HeTVAE includes a novel input layer to encode information about input observation sparsity, a temporal VAE architecture topropagate uncertainty due to input sparsity .…

Generating Large scale Dynamic Optimization Problem Instances Using the Generalized Moving Peaks Benchmark

This document describes the generalized moving peaks benchmark (GMPB) and how it can be used to generate problem instances for continuous large-scale dynamic optimization problems . It presents a set of 15 benchmark problems, the relevantsource code, and a performance indicator .…

A simple yet consistent constitutive law and mortar based layer coupling schemes for thermomechanical part scale simulations of metal additive manufacturing processes

This article proposes a coupled thermomechanical finite element modeltailored to the part-scale simulation of metal additive manufacturing process . A first focus lies on the derivation of aconsistent constitutive law on basis of a Voigt-type spatial homogenizationprocedure across the relevant phases, powder, melt and solid .…

On data lake architectures and metadata management

So-called big data generally come from transactionalsystems, and even more so from the Internet of Things and social media . A data lake is a large, raw data repository that stores and manages all company databearing any format . The data lake concept remains ambiguous or fuzzy for many researchers and practitioners, who often confuse it with the Hadoop technology .…

Technical Report Distributed Sampling based Planning for Non Myopic Active Information Gathering

This paper addresses the problem of active information gathering formulti-robot systems . The majority of existing information gathering approaches are centralized and, therefore, they cannot be applied to distributed robot teamswhere communication to a central user is not available . In our non-myopic approach, all robots build in parallellocal trees exploring the information space and their corresponding motionspace .…

Design of the Propulsion System of Nano satellite StudSat2

StudSat1, which was successfully launched on 12th July 2010, is the first Pico satellite developed in India by undergraduate students from seven different engineering colleges across South India . StudSat2 is India’s first twin satellite mission having twonanosatellites whose overall mass is less than 10kg .…

Machine Learning with a Reject Option A survey

Machine learning models always make a prediction, even when it is likely to be inaccurate . This behavior should be avoided in many decision support applications, where mistakes can have severe consequences . This machine learning subfield enables machine learning models toabstain from making a prediction when likely to make a mistake .…

Fastmultipole methods (FMM) are used to accelerate the matrix vector products needed . The method is based on recursions of themultipole moments for O(1) cost per moment with a low asymptotic constant . The derived recursions are tested both for accuracy and performance .… Joint Shapley values a measure of joint feature importance The Shapley value is one of the most widely used model-agnostic measures offeature importance in explainable AI . It has clear axiomatic foundations, is guaranteed to uniquely exist, and has a clear interpretation as a feature’saverage effect on a model’s prediction .… Remarks on lumping PageRank results of Ipsen and Selee By lumping all dangling nodes of a web graph into a single node, PageRankcomputation can be proceeded with a much smaller matrix on the case that thenumber of dangling nodes is large . Thus, it saves many computational cost and operations .… Implicit Rate Constrained Optimization of Non decomposable Objectives We consider a family of constrained optimization problems arising in machine learning that involve optimizing a non-decomposable evaluation metric with a certain thresholded form . We show how the resulting optimization problem can be solved using standard gradient based methods .… A Flexible Exoskeleton for Collision Resilience With inspiration from arthropods’ exoskeletons, we designed a simple, easilymanufactured, semi-rigid structure with flexible joints that can passively dampimpact energy . This exoskeleton fuses the protective shell to the main robotstructure, thereby minimizing its loss in payload capacity . Our design issimple to build and customize using cheap components and consumer-grade 3Dprinters .… Fabrication Aware Reverse Engineering for Carpentry We propose a novel method to generate fabrication blueprints from images of carpentered items . We demonstrate our method on a variety of wooden objects and furniture . We can automatically obtain designs that are both easy to edit and accurate recreations of the ground truth .… Bandit Quickest Changepoint Detection Detecting abrupt changes in temporal behavior patterns is of interest in many industrial and security applications . Abrupt changes are often local andobservable primarily through a well-aligned sensing action (e.g., a camera with a narrow field-of-view) Due to resource constraints, continuous monitoring of all of the sensors is impractical .… The Traveling Firefighter Problem The objective is to schedule a destination visit sequence for a traveler of unit speed to minimizethe Minkowskip$-norm of the resulting vector of visit/service times . For$p =\infty$the problem becomes a path variant of the TSP . We also study the all-norm-TSP problem [Golovin et al.… Testing isomorphism of chordal graphs of bounded leafage is fixed parameter tractable Every chordal graph can be represented as the intersection graph of some subtrees of a tree . The leafage of a chordalgraph, is defined to be the minimum number of leaves in the representing tree . We construct a fixed-parameter tractable algorithm testing isomorphism ofchordal graphs with bounded leafage .… Binary irreducible quasi cyclic parity check subcodes of Goppa codes and extended Goppa codes Goppa codes are particularly appealing for cryptographic applications . We present a sufficient and necessary condition for an irreducible monicpolynomial$g(x)$of degree$r$over$\mathbb{F}_{q}$satisfying$q=2^n$,$A=\left(\begin{array}{cc}a&b\\1&d\end{array}\right)\in PGL_2(\Bbb F_q)$is a prime,$g(a) is a . prime, and $0\ne \gamma\in… Nonlinear transformation of complex amplitudes via quantum singular value transformation Due to the linearity of quantum operations, it is not straightforward to implement nonlinear transformations on a quantum computer, making some tasks like a neural network hard to be achieved . In this work, wedefine a task called nonlinear transformation of complex amplitudes and provide an algorithm to achieve this task .… Multiclass versus Binary Differentially Private PAC Learning We show a generic reduction from multiclass differentially private PAClearning to binary private PAC learning . We apply this transformation to arecently proposed binary PAC learner to obtain a private multiclasslearner with sample complexity that has a polynomial dependence on themulticlass Littlestone dimension and a poly-logarithmic dependence on thenumber of classes .… Ready for Emerging Threats to Recommender Systems A Graph Convolution based Generative Shilling Attack Researchers propose novel shilling attack called Graph cOnvolution-based generativeshilling ATtack (GOAT) GOAT adopts the primitive attacks’ paradigm that assigns items for fake users by sampling . It deploys a generative adversarial network (GAN)that learns the real rating distribution to generate fake ratings .… CATE CAusality Tree Extractor from Natural Language Requirements Causal relations (If A, then B) are prevalent in requirements artifacts . We lack an approach capable of extracting causal relations from natural language with reasonable performance . In this paper, wepresent our tool CATE (CAusality Tree Extractor), which is able to parse thecomposition of a causal relation as a tree structure .… Fast Low Rank Tensor Decomposition by Ridge Leverage Score Sampling Low-rank tensor decomposition generalizes low-rank matrix approximation and is a powerful technique for discovering low-dimensional structure in high-dimensional data . We study Tucker decompositions and usetools from randomized numerical linear algebra called ridge leverage scores toaccelerate the core tensor update step in the widely-used alternating leastsquares (ALS) algorithm .… The Factors of Code Reviewing Process to Ensure Software Quality The effectiveness of the code review is that it ensures the quality of software and makes it updated . Code review is the best process that helps the developers to develop asystem errorless . This report contains two different code review papers to beevaluated and find the influences that can affect the code reviewing process .… Multi Stream Transformers Transformer-based encoder-decoder models produce a fused token-wiserepresentation after every encoder layer . We investigate the effects of allowing the encoder to preserve and explore alternative hypotheses, combined at the end of the encoding process . We design and examine a$\textit{Multi-stream Transformer}$architecture and find that splitting theTransformer encoder into multiple encoder streams and allowing the model to merge multiple representational hypotheses improves performance .… Shedding some light on Light Up with Artificial Intelligence The Light-Up puzzle, also known as the AKARI puzzle, has never been solved using modern artificial intelligence (AI) methods . This project is an effort to apply new AI techniques for solving the Light-up puzzle faster and more computationallyefficient . The algorithms explored for producing optimal solutions include hillclimbing, simulated annealing, feed-forward neural network (FNN), and CNN, and an evolutionary theory algorithm .… 3D Shape Generation with Grid based Implicit Functions Previous approaches to generate shapes in a 3D setting train a GAN on thelatent space of an autoencoder (AE) This produces convincing results, but it has two major shortcomings . To remedy these issues, we propose to train the GAN .… An Empirical Study on Code Comment Completion Code comments play a prominent role in program comprehension activities . But source code is not always documented and code and comments not alwaysco-evolve . To deal with these issues, researchers have proposed techniques toautomatically generate comments documenting a given code at hand .… The Stationary Prophet Inequality Problem We study a continuous and infinite time horizon counterpart to the classic prophet inequality problem . Buyers arrive similarly and make take-it-or-leave-it offers for unsold items . The objective is to maximize the (infinite) time average revenue of the seller .… CGuard Efficient Spatial Safety for C CGuard is a tool that provides object-bounds protection for C applications with comparable overheads to SGXBounds . CGuard stores bounds information just before the base address of an object and encodes the relative offset in the spare bits of the virtual address available in x86_64architecture .… High dimensional expansion implies amplified local testability In this work we show that high dimensional expansion implies locally testablecode . We define a notion that we callhigh-dimensional-expanding-system (HDE-system) We show that a code that can be modelled over HDE-system islocally testable . This implies that high-dimensional expansion phenomenon solely implies local testability of codes .… Joint Optimization of Preamble Selection and Access Barring for Random Access in MTC with General Device Activities Most existing random access schemes for MTC simply adopt a uniform preambleselection distribution, irrespective of the underlying device activitydistributions . We investigate three cases of the general joint device activity distribution . We formulate theaverage, worst-case average, and sample average throughput maximization maximization problems .… Fourier Reflexive Partitions Induced by Poset Metric Let$H$be the cartesian product of a family of finite abeliangroups indexed by a finite set . A given poset (i.e., partially orderedset) gives rise to a posetmetric on a given set . We prove that if$P} is Fourier-reflexive, then its dualpartition $Lambda$ coincides with the partition of the dual poset of $\mathbf{H$ .…

The general adwords problem has remained largely unresolved . We define asubcase called $k-TYPICAL,$k \in \Zplus$as follows: the total budgetof all the bidders is sufficient to buy$k\$ bids for each bidder . We also giverandomized online algorithms for other special cases of adwords .…