Curious Exploration and Return based Memory Restoration for Deep Reinforcement Learning

The proposed method can be utilized to train agents in environments with fairly complex state and action spaces . The main challenge of using such a rewardfunction is the high sparsity of positive reward signals . To address this problem, we use a simple prediction-based exploration strategy (called CuriousExploration) along with a Return-based Memory Restoration (RMR) technique which tends to remember more valuable memories .…

Weighted completion time minimization for capacitated parallel machines

We consider the weighted completion time minimization problem for capacitatedparallel machines . We bound its approximation ratio with a decreasing function of the ratio between the highest resource demand of any job to the server’s capacity . This research is the first, to the best of ourknowledge, to propose a polynomial-time algorithm with a constant approximationratio for minimizing the weighted sum of job completion times .…

Security Properties for Stack Safety

“stack safety” is associated with avariety of compiler, run-time, and hardware mechanisms for protecting stackmemory . We propose a formal characterization of stack safety, formulated with concepts from language-based security . We use these properties to validatethe stack-safety “micro-policies” proposed by Roessler and DeHon [2018].…

A Jointly Design for STAR RIS enhanced NOMA CoMP Networks A Simultaneously Signal Enhancement and Cancellation based SSECB Design

In this letter, a novel simultaneously transmitting and reflecting (STAR)reconfigurable intelligent surfaces (RISs) design is proposed in anon-orthogonal multiple access (NOMA) enhanced coordinated multi-pointtransmission (CoMP) network . We propose a novelsimultaneously-signal-enhancement-and-cancellation-based (SSECB) design, where the inter-cell interferences and desired signals can be simultaneouslyeliminated and boosted .…

AI Assisted MAC for Reconfigurable Intelligent Surface Aided Wireless Networks Challenges and Opportunities

Recently, significant research attention has been devoted to the study ofreconfigurable intelligent surfaces (RISs) RISs are capable of reconfiguring the wireless propagation environment by exploiting the unique properties ofmetamaterials-based integrated large arrays of inexpensive antennas . The medium access control (MAC) of multiple usersaccessing an RIS-enabled channel is still in its infancy, while many open issues remain to be addressed .…

Dialectica models of type theory

We present two Dialectica-like constructions for models of intensionalMartin-L\”of type theory . We propose a new semantic notion of finite sum for dependent types, generalizingfinitely-complete extensive categories . The second avoids extensivityassumptions using biproducts in a Kleisli category for a fibred additive monad .…

Deployment Archetypes for Cloud Applications

Survey paper explores six Cloud-based deployment archetypes to achieve highavailability, low end-user latency, and acceptable costs . These are (1) Zonal,(2) Regional, (3) Multi-Regional, (4) Global, (5) Hybrid, and (6) Multi Multi-Clouddeployment archetypes . This enables application owners to better examine the tradeoffsof each deployment model and what is needed for achieving the availability andlatency goals for their application .…

Properties of Graphs Specified by a Regular Language

Traditionally, graph algorithms get a single graph as input, and then they decide if this graph satisfies a certain property $Phi$ This question is modified in a way that we get a possibly infinite family ofgraphs as an input . We approach this question by using formal languages forspecifying families of graphs .…

Fast mixing via polymers for random graphs with unbounded degree

The polymer model framework is a classical tool from statistical mechanic . It has recently been used to obtain approximation algorithms for spin systemson classes of bounded-degree graphs . The edge perspective allows us to bound the growthrate of the number of polymers in terms of the total degree of the polymers, which in turn can be related more easily to the expansion properties of the underlying graph .…

Probabilistic Analysis of Operating Modes in Cache Enabled Full Duplex D2D Networks

Cache-enabled Device-to-Device (D2D) communication is one of the key enablers of the fifth generation (5G) cellular network . But conventional half-duplex(HD) communication may not be sufficient to provide fast enough content delivery over D2D links . In-band full-duple (FD) can provide more content deliveryopportunities, thus resulting improved spectral efficiency and latency reduction .…

Cross Modal Self Attention with Multi Task Pre Training for Medical Visual Question Answering

Existing methods of medical visual question answering usually rely on transfer learning to obtain effective image feature representation . We introduce a cross-modal self-attention module to capture the long-range contextual relevance for more effectivefusion of visual and linguistic features . Experimental results demonstrate that the proposed method outperforms existing state-of-the-art methods .…

BI REC Guided Data Analysis for Conversational Business Intelligence

BI-REC is a conversational recommendation system for BI applications to help users accomplish their data analysis tasks . We define the space of data analysis in terms of BI patterns, augmented with rich semantic information extracted from the OLAP cube definition, and usegraph embeddings learned using GraphSAGE to create a compact representation of the analysis state .…

Rate Splitting Multiple Access for Enhanced URLLC and eMBB in 6G

Rate-Splitting Multiple Access (RSMA) is a flexible and robust multipleaccess scheme for downlink multi-antenna wireless networks . RSMA relies onRate-splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at receivers . We present the optimal system designsemploying RSMA that target short-packet and low-latency communications as well as robust communications with high-throughput under the practical and importantsetup of imperfect Channel State Information at Transmitter (CSIT) originating from user mobility and feedback latency in the network .…

Intelligent Reflecting Surface Assisted Secret Key Generation In Multi antenna Network

Physical-layer key generation (PKG) can generate symmetric keys between twocommunication ends based on the reciprocal uplink and downlink channels . Bysmartly reconfiguring the radio signal propagation, intelligent reflectingsurface (IRS) is able to improve the secret key rate of PKG . IRS-assistedmultiple-input single-output (MISO) system aims to maximize the secretkey rate by optimally designing the IRS passive beamforming .…

What Way Is It Meant To Be Played

The most commonly used interface between a video game and a human user is a “game controller” We present simple formats for such mappings as well as constraints on possible inputs which are determined by a physical controller or required to be met for a game software, along with methodsto transform said constraints via a button-action mapping and to check oneconstraint set against another, i.e.…

Lecture Notes on Voting Theory

Lectures were developed for the course Computational SocialChoice of the Artificial Intelligence MSc programme at the University of Groningen . They cover mathematical and algorithmic aspects of voting theory .…

Adapting CRISP DM for Idea Mining A Data Mining Process for Generating Ideas Using a Textual Dataset

Data mining project managers can benefit from using standard data miningprocess models . The CRISP-IM facilitates idea generation, through theuse of Dynamic Topic Modeling (DTM) and unsupervised machine learning, and statistical analysis on a dataset of scholarly articles. The adaptedCRISp-IM can be used to guide the process of identifying trends using scholarlyliterature datasets or temporally organized patent or any other textual dataset to elicit ideas.…

Paradiseo From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics 22 Years of Paradiseo

ParadisEO is a comprehensive C++ freesoftware which targets the development of modular metaheuristics . It is of prior importance to have access to mature and flexible software frameworks which allow for an efficient exploration of the algorithm design space . This articlesummarizes the features of the framework, a highly modular architecture, a large set of components, speed of execution and automated algorithm design features, which are key to modern approaches to metaheiristics development .…

Data Driven Model Order Reduction for Problems with Parameter Dependent Jump Discontinuities

We propose a data-driven model order reduction (MOR) technique for partial differential equations that exhibit parameter-dependentjump-discontinuities . We build upon themethodology of approximating the map between the parameter domain and theexpansion coefficients of the reduced basis via regression . The online stagequeries the regression model for the expansion coefficients and recovers areduced approximation for the solution .…

Fixed Point Constructions in Tilings and Cellular Automata

Fixed point construction is a method for designing tile sets and cellularautomata with highly nontrivial dynamical and computational properties . It produces an infinite hierarchy of systems where each layer simulates the nextone . The simulations are implemented entirely by computations of Turingmachines embedded in the tilings or spacetime diagrams .…

Graph Vulnerability and Robustness A Survey

The study of network robustness is a critical tool in the characterizationand sense making of complex interconnected systems such as infrastructure,communication and social networks . This survey guides researchers and practitioners in navigating theexpansive field, while summarizing answers to key questions .…

Estimating the electrical power output of industrial devices with end to end time series classification in the presence of label noise

The proposed approach targets to gradually correct themislabelled data samples during training in a self-supervised fashion, without any prior assumption on the amount of label noise . We benchmark our approach on several time-series classification datasets and find it to be comparable and sometimes better than state-of-the-art methods .…

Data driven discovery of physical laws with human understandable deep learning

There is an opportunity for deep learning to revolutionize science and technology by revealing its findings in a human interpretable manner . Wedevelop a novel data-driven approach for creating a human-machine partnershipto accelerate scientific discovery . By collecting physical system responses,under carefully selected excitations, we train rational neural networks tolearn Green’s functions of hidden partial differential equation .…

Model Checking Quantum Continuous Time Markov Chains

A real-time system, we specify the temporal properties on QCTMC by signal temporal logic (STL) To effectivelycheck the atomic propositions in STL, we develop a state-of-art real rootisolation algorithm under Schanuel’s conjecture . Further, we check the generalSTL formula by interval operations with a bottom-up fashion, whose querycomplexity turns out to be linear in the size of the input formula by calling the real root isolation algorithm .…

Benchmarking as Empirical Standard in Software Engineering Research

In empirical software engineering, benchmarks can be used for comparing methods, techniques and tools . The recent ACM SIGSOFTEmpirical Standards for Software Engineering Research do not include an explicit checklist for benchmarking . In this paper, we discuss benchmarks forsoftware performance and scalability evaluation as example research areas in software engineering .…

Child Robot Interaction Studies During COVID 19 Pandemic

The coronavirus disease (COVID-19) pandemic affected our lives deeply, just like everyone else, justlike everyone else . The children also suffered from the restrictions due to the restrictions . The precautions due to COVirus disease also introduced new constraints in the social robotics research .…