On guarding polygons with holes

There is an old conjecture by Shermer \cite{sher} that in a polygon with $n$vertices and $h$ holes, the guards aresufficient to guard the entire polygon . In this paper, we prove a theorem similar to the Shermer’s conjecture for aspecial case where the goal is to guard vertices of the polygon (not theentire polygon) which is equivalent to finding a dominating set for thevisibility graph .…

WaNet Imperceptible Warping based Backdoor Attack

The proposed backdoor outperforms the previous methods in a human inspection test by a wide margin, proving its stealthiness . Backdoor attacks are all built on noise perturbation triggers, making them noticeable to humans . To make such models undetectable by machine defenders, we propose a novel training mode, called the “noise mode .…

An ecologically valid examination of event based and time based prospective memory using immersive virtual reality the effects of delay and task type on everyday prospective memory

Recent research has focused on assessing either event- or time-basedprospective memory (PM) using laboratory tasks . Yet, the findings pertaining to PM performance on laboratory tasks are often inconsistent with the findings on naturalistic experiments . The Virtual Reality Everyday Assessment Lab(VR-EAL) was implemented to comprehensively assess everyday PM(i.e.e.,…

Stability and Resilience of Distributed Information Spreading in Aggregate Computing

Spreading information through a network of devices is a core activity formost distributed systems . Self-stabilizing algorithms implementinginformation spreading are one of the key building blocks enabling aggregatecomputing to provide resilient coordination in open complex distributedsystems . The ultimate bounds dependonly on the magnitude of the largest perturbation and the network diameter, and three design parameters trade off competing aspects of performance .…

Making an H Free Graph k Colorable

We study the question: How few edges can we delete from any$H$-free graph on $n$ vertices in order to make the resulting graph$k$-colorable? It turns out that various classical problems in extremal graphtheory are special cases of this question . We prove an upper bound when $H$ is a fixed clique that we conjecture istight up to a constant factor, and prove upper bounds for more general familiesof graphs .…

Byzantine Agreement with Unknown Participants and Failures

A set of mutually distrusting participants that want to agree on a common opinion must solve an instance of a Byzantine agreement problem . Most of the existingsolutions assume that the participants are aware of $n$ — the total number of participants in the system — and $f$ — an upper bound on the number ofByzantine participants .…

ALTO Adaptive Linearized Storage of Sparse Tensors

Real-world sparse tensors are challenging to process due to their irregular shapes and data distributions . We propose theAdaptive Linearized Tensor Order (ALTO) format . ALTO achieves a geometricmean speedup of 8X over the best mode-agnostic format, while delivering ageometric mean compression ratio of more than 4X relative to the bestmode-specific format .…

Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application Evidence from Econometric Models and Machine Learning Instruments

In this paper, we examine the effectiveness of various recommendationstrategies in the mobile channel . We find significant differences ineffectiveness among various recommendation strategies . Interestingly,recommendation strategies that directly embed social proofs for the recommendedalternatives outperform other recommendations . We also facilitate the estimation of causal effects in the presence of endogeneity using machine-learning methods .…

An unbiased ray marching transmittance estimator

We present an in-depth analysis of the sources of variance in unbiased volumetric transmittance estimators . We also propose new methods for improving their efficiency . These combine to produce asingle estimator that is universally optimal relative to prior work, with up toseveral orders of magnitude lower variance at the same cost, and has zerovariance for any ray with non-varying extinction .…

Online Stochastic Max Weight Bipartite Matching Beyond Prophet Inequalities

We present a polynomial-time algorithm which approximates optimal onlinewithin a factor of $0.51$ beating the best-possible prophet inequality . In contrast, we show that it is PSPACE-hard to approximate this problem within some constant $\alpha< 1$ The problem was recently introduced by Ezra, Feldman, Gravin and Tang (EC'20), who gave a $1/2$-competitive algorithm for it . At thecore of our result are a new linear program formulation, an algorithm that tries to match the arriving vertices in two attempts, and an analysis that bounds the correlation resulting from the second attempts . This is the best possible ratio,as this problem is a generalization of the original single-item prophetinequality. This problem is the generalization, as this problem was a generalizing of the . problem is generalized of the old single- …

All Chalcogenide Programmable All Optical Deep Neural Networks

All-optical neural networkswithout any electro-optic conversions could alleviate these shortcomings . Optical neural networks that bypass electrooptic conversionaltogether hold promise for network-edge machine learning applications such as for autonomous vehicles ornavigation systems such as signal pre-processing of LIDAR systems . We show how the structural phasetransitions in a wide-bandgap phase-change material enables storing the neuralnetwork weights via non-volatile photonic memory, whilst resonant bonddestabilisation is used as a nonlinear activation threshold without changing the material .…

Mechanism Design Powered by Social Interactions

Mechanism design has traditionally assumed that the set of participants are fixed and known to the mechanism (the market owner) in advance . However, in practice, the market owner can only directly reach a small number of participants (her neighbours) The owner often needs costly promotions to recruit more participants in order to get desirable outcomes such as social welfare or revenue maximization .…

Simplest Non Regular Deterministic Context Free Language

A problem is C-simpleif it can be reduced to each problem in C . This can be viewed as a conceptualcounterpart to C-hard problems to which all problems in C reduce . Our concreteexample is the class of non-regular deterministic deterministic context-free languages(DCFL’), with a truth-table reduction by Mealy machines .…

Sim Env Decoupling OpenAI Gym Environments from Simulation Models

Reinforcement learning (RL) is one of the most active fields of AI research . Despite interest demonstrated by the research community in reinforcementlearning, the development methodology still lags behind . The Sim-Env Pythonlibrary generates OpenAI-Gym-compatible reinforcement learning environmentsthat use existing or purposely created domain models as their simulationback-ends .…

Clarification of Video Retrieval Query Results by the Automated Insertion of Supporting Shots

Computational Video Editing Systems output video generally follows aparticular form, e.g. conversation or music videos, in this way they are domainspecific . We describe a recent development in our video annotation and segmentation system to support general computational video editing in which wederive a single generic editing strategy from general cinema narrativeprinciples instead of using a hierarchical film gram-mar .…

Crowbar Behavioral Symbolic Execution for Deductive Verification of Active Objects

Crowbar is a deductive verification system for the ABSlanguage . Crowbar models distributed systems with the Active Object concurrencymodel . Each method issymbolically executed, but specification and prior static analyses influencethe shape of the symbolic execution tree . User interaction is realized throughguided counterexamples, which present failed proof branches in terms of the input program.…

MHDeep Mental Health Disorder Detection System based on Body Area and Deep Neural Networks

Mental health problems impact quality of life of millions of people around the world . Diagnosis of mental health disorders is a challenging problem that often relies on self-reporting by patients . MHDeep uses body-area networks consisting of aplethora of accurate sensors embedded in smartwatches and smartphones and deepneural networks (DNNs) points towards a possible solution .…

GIST Distributed Training for Large Scale Graph Convolutional Networks

GIST is a hybrid layer and graphsampling method, which disjointly partitions the global model into several,smaller sub-GCNs that are independently trained across multiple GPUs in parallel . This distributed framework improves model performance and significantly decreases wall-clock training time . GIST seeks to enable large-scale GCN experimentation with the goal of bridging the existing gap inscale between graph machine learning and deep learning .…

Automatic Programming Through Combinatorial Evolution

Only a few iterations seem to be required to already achieve complex objects . Computers generate computer programs of increasing complexity through combinatorial evolution . Combinatorial evolution seems to be a promising approach for automatic programming, authors say . We found that reserved key words of a programming language are suitable for defining the basic code blocks at the beginning of the simulation.…

Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Systems

With the introduction of 5G networks and the advancement of intechnologies, new and emerging networking technologies and use cases are takingshape . Federated Learning, a collaborative and distributed intelligence technique, is suggested . With the ability of a federated model deployed on roadside infrastructure throughout the network, leveraging group intelligence while reducing recoverytime and restoring acceptable system performance is highlighted .…

Merly jl Web Framework in Julia

Merly.jl is a package for creating web applications in Julia . It presents a familiar syntax with the rest of the most popular web frameworks without neglecting the execution performance . This manuscript mentions the operation and main features of the main feature of the package .…

TransMask A Compact and Fast Speech Separation Model Based on Transformer

Speech separation is an important problem in speech processing, which targetsto separate and generate clean speech from a mixed audio containing speech from different speakers . By fully un-leashing the power of self-attention on long-term dependency exception, we demonstrate the size of TransMask is morethan 60% smaller and the inference is more than 2 times faster than state-of-the-art solutions .…

FLACK Counterexample Guided Fault Localization for Alloy Models

FLACK is a tool that takes as input an Alloy model consisting of some violated assertion . It returns a ranked list of suspicious expressions contributing to the assertion violation . The tool is efficient (can handle complex, real-world Alloymodels with thousand lines of code within 5 seconds) FLACK can be useful (can often narrow down the error to the exact location within the suspicious expressions).…

A theory of capacity and sparse neural encoding

We study sparse neural maps from an input layer to a target layer with sparse activity . We mathematically prove that $K$ undergoes a phase transition and that sparsity inthe target layers increases the storage capacity of the map . The target vectors can be chosen arbitrarily, including in random fashion, and the memories can be encoded and decoded by networks trained using local learning rules .…

Towards Teachable Conversational Agents

The traditional process of building interactive machine learning systems can be viewed as a teacher-learner interaction scenario . In this work, we explore the idea of using a conversational interface to investigate the interaction between human-teachers and interactive machine-learners . Results validate the concept of teachable AI agents and highlight the factors relevant for the development of machine-learning systems that intend to learn from conversational interactions, such as human-learning algorithms .…

Design Patterns for Blockchain Based Payment Applications

Blockchain technology facilitates fast, secure, and cross-border payments without the need for intermediaries such as banks . As the killer application of blockchain technology, blockchain-based payments have attracted extensive attention ranging from hobbyists to corporates toregulatory bodies . We present 15 design patterns that cover critical aspects in enabling the state transitions of a token in blockchain-related payment applications .…

Kokkos Kernels Performance Portable Sparse Dense Linear Algebra and Graph Kernels

Kokkos Kernels is a library of kernels that serve the needs of several CSE applications and software frameworks . Wedescribe the design principles of such a library and demonstrate portableperformance of the library using some selected kernels . Specifically, wedemonstrate the performance of four sparse kernels, three dense batchedkernels, two graph kernels and one team level algorithm.…

Principled Simplicial Neural Networks for Trajectory Prediction

We consider the construction of neural network architectures for data onsimplicial complexes . In studying maps on the chain complex of a simplicialcomplex, we define three desirable properties of a neural networkarchitecture . The last property encodes the desirable feature that the output of the neural network depends on the entire simplicial complex and not on a subset of its dimensions .…