Non Invertible Element Constacyclic Codes over Finite PIRs

In this paper we introduce the notion of $\lambda$-constacyclic codes overfinite rings $R$ for arbitary element $R$. We study thenon-invertible-element constacyClic codes (NIE-consticclic code) over finiteprincipal ideal rings (PIRs) We determine the algebraic structures of all NIE codes over finite chain rings, give the unique form of thesets of the defining polynomials and obtain their minimum Hamming distances .…

Stability of Discontinuous Galerkin Spectral Element Schemes for Wave Propagation when the Coefficient Matrices have Jumps

We use the behavior of the $L_{2}$ norm of the solutions of linear hyperbolicequations with discontinuous coefficient matrices as a surrogate to inferstability of discontinuous Galerkin spectral element methods (DGSEM) We show that the DGSEM with an upwind numerical flux that satisfies the Rankine-Hugoniot (or conservation) condition has the same energy bound as the partial differential equation does in $L_2$ norm, plus an added addeddissipation that depends on how much the approximate solution fails to satisfy the conservation condition .…

Fractional Matchings under Preferences Stability and Optimality

We study a generalized version of the classic Stable Marriage and Stable Roommates problems where agents may share partners . We consider twoprominent stability concepts: ordinal stability [Aharoni and Fleiner, Journalof Combinatorial Theory, 2003] and cardinal stability [Caragiannis et al., ACMEC 2019] and two optimality criteria: maximizing social welfare (i.e.…

Interpretable Models in ANNs

Artificial neural networks are often very complex and too deep for a human to understand . In this paper, we try to find a way to explain anetwork and extract a human-readable equation that describes the model . In some cases, laws of physics, for example, the pattern can be described by relatively simplemathematical expressions .…

Deep learning based discovery of partial differential equations in integral form from sparse and noisy data

Data-driven discovery of partial differential equations (PDEs) has attracted attention in recent years . For PDEs with high-orderderivatives, the performance of existing methods is unsatisfactory, especially when the data is sparse and noisy . New framework combining deep-learning and integral form is proposed to handle the above-mentionedproblems simultaneously, and improve the accuracy and stability of PDEdiscovery .…

Lethean Attack An Online Data Poisoning Technique

Data poisoning is an adversarial scenario where an attacker feeds a speciallycrafted sequence of samples to an online model in order to subvert learning . We apply the attack in the contextof Test-Time Training, a modern online learning framework aimed forgeneralization under distribution shifts .…

Stochastic sparse adversarial attacks

Stochastic sparse adversarial attacks (SSAA) are simple, fast and purely noise-based targeted and untargeted attacks of NNC . SSAA offer new examples of sparse (or $L_0$) attacks for which only few methodshave been proposed previously . These attacks are devised by exploiting asmall-time expansion idea widely used for Markov processes .…

CCIC WSN An Architecture for Single Channel Cluster based Information Centric Wireless Sensor Networks

Named Data Networking (NDN) has attracted extensive attention in the context of the Internet of Things (IoT) and Wireless SensorNetworks (WSNs) A comprehensive NDN/ICN-based architectural designfor WSNs has yet to be explored . In this paper, we present single-ChannelCluster-based Information-Centric WSN (CCIC-WSN) We demonstrate that CCIC-wSNachieves 71-90% lower energy consumption and 74-96% lower data retrieval delay .…

C Learning Horizon Aware Cumulative Accessibility Estimation

Multi-goal reaching is an important problem in reinforcement learning needed to achieve algorithmic generalization . Current algorithms suffer from high sample complexity, learning only a single way of reaching the goals, and difficulties in solving complex motion planning tasks . We show that our method outperforms state-of-the-art goal-reaching algorithms in success rate, sample complexity and path optimality .…

General Purpose Atomic Crosschain Transactions

The General Purpose Atomic Crosschain Transaction protocol allows composableprogramming across multiple Ethereum blockchains . It allows for inter-contractand inter-blockchain function calls that are both synchronous and atomic . If one part fails, the whole call graph of function calls is rolled back .…

Zero Shot Visual Slot Filling as Question Answering

This paper presents a new approach to visual zero-shot slot filling . The approach extends previous approaches by reformulating the slot filling task asQuestion Answering . The multi-task approach facilitates the incorporation of a large number of refinements and transfer learning across similar tasks .…

Min Sum Clustering with Outliers

We give a constant factor polynomial time pseudo-approximation algorithm formin-sum clustering with or without outliers . The algorithm is allowed to exclude an arbitrarily small constant fraction of the points . Our results apply to instances of points in real space, as well as to points in a metricspace, where the number of clusters, and also the dimension if relevant, isarbitrary (part of the input, not an absolute constant) The approximation guarantee growswith $\frac{1-\eps) n’$ points .…

Envy Free Allocations Respecting Social Networks

Finding an envy-free allocation of indivisible resources to agents is acentral task in many multiagent systems . Classical envy-freeness requires that every agent likesthe resources allocated to it at least as much as those allocated to any other agent . In many situations this assumption can be relaxed since agentsoften do not even know each other .…

Model Elicitation through Direct Questioning

Teammates interact, and the robot’s interaction has to be about getting useful information about the human’s(teammate’s) model . There are many challenges before a robot can interact, suchas incorporating the structural differences in the human model, ensuringsimpler responses, etc. The evaluation shows that these questions can be generated offline, and can help refine the model through simple answers .…

Solving Two Dimensional H curl elliptic Interface Systems with Optimal Convergence On Unfitted Meshes

In this article, we develop and analyze a finite element method with the first family N\’ed\’elec elements of the lowest degree for solving a Maxwellinterface problem . We establish a few important properties for the IFEfunctions including the unisolvence according to the edge degrees of freedom, the exact sequence relating to the $H^1$ IFE functions and the optimalapproximation capabilities .…

Exploring the landscapes of computing digital neuromorphic unconventional and beyond

The acceleration race of digital computing technologies seems to be steeringtoward impasses — technological, economical and environmental — a condition that has spurred research efforts in alternative, “neuromorphic” (brain-like)computing technologies . The idea of exploiting nonlinear physical phenomena “directly” for non-digital computing has been explored under names like “unconventional computing”, “natural computing”,”physical computing”, or “in-materio computing” I stake out how a general concept of “computing” can bedeveloped which comprises digital, neuromorphic, unconventional and possible future paradigms .…

Reinforced optimal control

Least squares Monte Carlo methods are a popular numerical approximationmethod for solving stochastic control problems . The choice of basis functions is crucial for the accuracy of the method . We extend the reinforced regression method to a generalclass of stochastically control problems, while considerably improving the method’s efficiency .…

Energy Efficient Resource Allocation in Multi UAV Assisted Two Stage Edge Computing for Beyond 5G Networks

Unmanned aerial vehicle (UAV)-assisted multi-access edge computing (MEC) has become one promising solution for energy-constrained devices . We formulate a joint task offloading, communication and computation resource allocationproblem to minimize the energy consumption of MDs and UAVs by considering the limited communication resources for the uplink transmission, the computation resources of UAV and the computation of the tasks .…

Dual Supervision Framework for Relation Extraction with Distant Supervision and Human Annotation

Relation extraction (RE) has been extensively studied due to its importance in real-world applications such as knowledge base construction and questionanswering . Most of the existing works train the models on either distantlysupervised data or human-annotated data . To take advantage of the high accuracy of human annotation and the cheap cost of distant supervision, we propose thedual supervision framework .…

Low Complexity Precoding and Detection in Multi user Massive MIMO OTFS Downlink

Orthogonal Time Frequency Space (OTFS) modulation has been shown tobe robust to channel induced Doppler spread . In OTFS based systems, informationsymbols are embedded in the delay-Doppler (DD) domain where they are jointlymodulated to generate the time-domain transmit signal . The complexity of the proposedprecoder increases only linearly with increasing number of BS antennas Q and thenumber of UTs .…

On the Serverless Nature of Blockchains and Smart Contracts

Serverless architecture is more frequently associated with the architectural style for developing cloud-native applications . Blockchains are distributed systems designed to enable collaborative scenarios involving untrusted parties . The decentralizedpeer-to-peer nature of blockchains makes it interesting to consider them inserverless architectures, since resource allocation and management tasks are not required to be performed by users .…