Spatio temporal Graph RNN for Point Cloud Prediction

In this paper, we propose an end-to-end learning network aim at predicting future PC frames, based on point-based RNN network . As main novelty, an initiallayer learns topological information of point clouds as geometric features and then uses the learned features to form representative spatio-temporalneighborhoods .…

Holographic Cell Stiffness Mapping Using Acoustic Stimulation

Cell stiffness is one of the fundamental mechanical properties of the cell and is greatly affected by the intracellular tensional forces, cytoskeletalprestress, and cytoskeleton structure . Accurate assessment of stiffness distribution is essential due to the critical role of single cell mechanobiology in the regulation of many vital processes such as proliferation, adhesion, migration, and motility .…

OmniDet Surround View Cameras based Multi task Visual Perception Network for Autonomous Driving

Surround View fisheye cameras are commonly deployed in automated driving for360\deg{} near-field sensing around the vehicle . This work presents amulti-task visual perception network . It consists of six primarytasks necessary for an autonomous driving system: depth estimation, visualodometry, semantic segmentation, motion segmentation and object detection, and lens soiling detection .…

Generation for adaption a Gan based approach for 3D Domain Adaption inPoint Cloud

Recent deep networks have achieved good performance on a variety of 3d points classification tasks . However, these models often face challenges in “wildtasks” Unsupervised domain adaptation (UDA) seeks to overcome such a problem without target domain labels . Instead of aligning features betweensource data and target data, we propose a method that use a Generativeadversarial network to generate synthetic data from the source domain so that the output is close to the target domain .…

Maximizing Joint Entropy for Batch Mode Active Learning of Perceptual Metrics

Active metric learning is the problem of incrementally selecting batches of training data (typically, ordered triplets) to annotate, in order toprogressively improve a learned model of a metric over some input domain asrapidly as possible . Standard approaches, which independently select eachtriplet in a batch, are susceptible to highly correlated batches with many redundant triplets and hence low overall utility .…

Capturing Detailed Deformations of Moving Human Bodies

New method to capture detailed human motion, sampling more than1000 unique points on the body . Our method outputs highly accurate 4D(spatio-temporal) point coordinates and, crucially, automatically assigns aunique label to each of the points . The locations and unique labels of thepoints are inferred from individual 2D input images only, without relying on any human body shape or skeletal kinematics models .…

A Tale of Three Datasets Towards Characterizing Mobile Broadband Access in the United States

Understanding and improving mobile broadband deployment is critical tobridging the digital divide and targeting future investments . In 2019, the Federal CommunicationsCommission (FCC) released a report on the progress of mobile broadbanddeployment in the United States . This report received a significant amount ofcriticism with claims that the cellular coverage, mainly available throughLong-Term Evolution (LTE), was over-reported in some areas, especially rural and/or tribal areas .…

Simulation based Optimization and Sensibility Analysis of MPI Applications Variability Matters

Finely tuning MPI applications and understanding the influence of keyparameters is critical . We demonstrate the capability of our method withHigh-PerformanceLinpack (HPL), the benchmark used to rank supercomputers intheTOP500, which requires careful tuning . We present an extensive (in)validation study that compares simulation with realexperiments and demonstrates our ability to predict the performance of HPL within a few percent consistently .…

A first look into the carbon footprint of federated learning

Federated Learning (FL) is starting to be deployed at a global scale by companies that must adhere to new legal demands and policies for privacy protection . Despite impressive results, deep learning-based technologies also raisesevere privacy and environmental concerns . This paper offers the first-ever systematic study of the carbon footprint of FL .…

Byzantine Dispersion on Graphs

The problem of Byzantine dispersion asks: given $n$ robots, up to $f$ of which are Byzantine, placed arbitrarily on an anonymous graph, design a terminating algorithm to be run by the robots . Each node has atmost one non-Byzantine robot on it .…

Large coverage fluctuations in Google Scholar a case study

This study analyses a large decrease incoverage of documents in the field of Astronomy and Astrophysics that took place in 2019 and its subsequent recovery, using longitudinal data from previous analyses and a new dataset extracted in 2020 . Disappeared documents did not reappear until the following index-wide update, many months after the problem was discovered .…

Expansions in Cantor real bases

We introduce and study series expansions of real numbers with an arbitraryCantor real base . We pay special attention to periodic Cantor real bases, which we callalternate bases . We prove a generalization of Parry’s theorem characterizingsequences of nonnegative integers that are the greedy$\boldsymbol{\beta$-representations of some real number in the interval$[0,1)$.…

Preimages under the Queuesort algorithm

Following the footprints of what have been done with the algorithm Stacksort, we investigate the preimages of the map associated with a slightly less wellknown algorithm, called Queuesort . We provide a recursion description of the set of all preimages, which can be also translated into a recursive procedure to find such preimages .…

Local Access to Random Walks

For a graph $G$ on $n$ vertices, naively sampling the position of a randomwalk of at time $t$ requires work $Omega(t)$. We desire local accessalgorithms supporting $O}(G,s,t) queries, which return theposition of a . random walk from some start . $s$ at time of a walk, where the joint distribution of returned positions is $1/\text{poly}(n)$ close to theuniform distribution over such walks in $ell_1$ distance .…

Dynamic Membership for Regular Languages

We study the dynamic membership problem for regular languages: fix a languageL, read a word w, build in time O(|w|) a data structure indicating if w is inL, and maintain this structure efficiently under substitution edits on w . We show that the problem is in O(log log |w| / log log | w|) for languages in analgebraically-defined class QSG .…

Testing properties of signed graphs

In graph property testing the task is to distinguish whether a graphsatisfies a given property or is “far” from having that property . In this work we initiate the studyof property testing in signed graphs, where every edge has either a positive or negative sign .…

Learning Pomset Automata

We extend the L* algorithm to learn bimonoids recognising pomset languages . We then identify a class of automata that accepts precisely the class of pomsets languages recognised by pimonoids .…

On synthesizing Skolem functions for first order logic formulae

Skolem functions play a central role in logic, from eliminating quantifiers in first order logic formulas to providing functional implementations ofrelational specifications . The question of how to effectively compute them is also important and useful for several applications . We show that even under reasonable assumptions on the signature of the formula, it is impossible to compute or synthesize SkoleM functions .…

Model bounded monitoring of hybrid systems

Monitoring of hybrid systems attracts both scientific and practicalattention . We introduce a model-bounded monitoring scheme, where we useprior knowledge about the target system to prune interpolation candidates . We present two partial algorithms – one isvia reduction to reachability in LHAs and the other is a direct one usingpolyhedra – and show that these methods are efficient and practically relevant .…

MatchKAT An Algebraic Foundation For Match Action

We present MatchKAT, an algebraic language for modeling match-action packetprocessing in network switches . We hope to embark on the first steps in exploring how networkprograms compiled to match-actions can be reasoned about formally in areliable, algebraic way . We alsodemonstrate the complexity of deciding equivalence in MatchKat isPSPACE-complete .…

A NeRF Surface free Human 3D Pose Refinement via Neural Rendering

We propose a novel test-time optimizationapproach for monocular motion capture that learns a volumetric body model of the user in a self-supervised manner . Our proposed skeleton embedding serves as a common referencethat links constraints across time, thereby reducing the number of required camera views from traditionally dozens of calibrated cameras, down to a singleuncalibrated one .…

An Overview of Agent based Traffic Simulators

Computer-based simulation is an accepted means for investigating the effects of new transportation policies and services . In most countries population in urban areas is growing, while availabletravel infrastructure and resources are limited . At the same time desires tominimise environmental impact and energy use have led to new requirements inthe field of inner-city transportation .…

Tight Revenue Gaps among Multi Unit Mechanisms

This paper considers Bayesian revenue maximization in the $k$-unit setting . Four basicmechanisms among others have been widely employed in practice and widelystudied in the literature . We investigate the largest possible ratio between the two revenues (a.k.a.\ the revenue gap), overall possible value distributions of the buyers .…

Selecting Matchings via Multiwinner Voting How Structure Defeats a Large Candidate Space

Given a set of agents with approval preferences over each other, we study the task of finding $k$ matchings fairly representing everyone’s preferences . We show that proportional approval voting (PAV), a well-establishedbut computationally intractable voting rule, becomes polynomial-timecomputable, and its sequential variant (seq-PAV) fulfills a rather strong guarantee known as extended justified representation .…

Log time Prediction Markets for Interval Securities

We design a prediction market to recover a complete and fully general probability distribution over a random variable . Traders buy and sell intervalsecurities that pay $1 if the outcome falls into an interval and $0 otherwise . Our first design replicates the popular logarithmic market scoring rule (LMSR) but operates exponentially faster than a standard LMSR .…

Self Organizing Teams in Online Work Settings

Self-Organizing Teams (SOTs) relies on the crowd of online workers itself to organize into effective teams . Depriving users of control over who they work with stifles creativity and causes psychological discomfort, authors say . SOTs are a new human-centered computational structure, which enables participants to control, correct and guide the output of their collaboration as a collective .…

Confidence Aware Learning Assistant

A system that estimates self-confidence while solving multiple-choice questions by eye tracking and gives feedback about which question should be reviewed carefully . We report the results of three studies measuring its effectiveness . Correct answer rates of questions were increased by 14% and 17% by giving feedback about correct answers without confidence and incorrectanswers with confidence, respectively .…

Human Robot Handshaking A Review

Shaking hands is a simple, natural interaction usedcommonly in many social contexts and is seen as a symbol of greeting, farewelland congratulations . In this paper, we take a look at the existing state of Human-Robot Handshaking research . We mainly see that some form of synchronisation exists during the different phases of the interaction .…

UserReg A Simple but Strong Model for Rating Prediction

Collaborative filtering (CF) has achieved great success in the field of collaborative filtering . Many newly proposed models are not as strong as expected and outperformed by very simple baselines . Paper proposes a simple linear model based on Matrix Factorization (MF),called UserReg, which regularizes users’ latent representations with explicit feedback information for rating prediction .…