ICodeNet A Hierarchical Neural Network Approach for Source Code Author Identification

ICodeNet consists of an ImageNet trainedVGG encoder followed by a shallow neural network . The shallow network is based on either CNN or LSTM . Different variations of models are evaluated on a sourcecode author classification dataset . We have also compared our image-basedhierarchical neural network model with simple image-freezing CNN architecture and text-based CNN and L STM models to highlight its novelty and efficiency.…

Classification of Fracture and Normal Shoulder Bone X Ray Images Using Ensemble and Transfer Learning With Deep Learning Models Based on Convolutional Neural Networks

Shoulder boneXray images were classified and compared via deep learning models based onconvolutional neural network (CNN) using transfer learning and ensemblelearning . The study was conducted using all shoulder images in musculoskeletal radiographs (MURA) dataset, one of the largest publicradiographic image datasets .…

A Trust Based Approach for Volunteer Based Distributed Computing in the Context of Biological Simulation

A trust-based approach uses trusted communities that are a subset of all clients where they trust each other . Using such TCs, the system becomes more organic and responds better to malicious or malfunctioning clients . This approach is more organic than previous attempts to simulate complex biological processes, such as the creation of a computer that simulates biological processes such as those of nature .…

Towards Imperceptible Query limited Adversarial Attacks with Perceptual Feature Fidelity Loss

Recently, there has been a large amount of work towards fooling deep-learning-based classifiers . However, researchers usually use Lp-norm minimization as a proxy for imperceptibility, which oversimplifies the diversity and richness of real-world images and human visual perception . The metric is particularly useful inthe challenging black-box attack with limited queries, where theimperceptibility is hard to achieve due to the non-trivial perturbation power.…

Shapley Scarf Housing Markets Respecting Improvement Integer Programming and Kidney Exchange

In a housing market of Shapley and Scarf, each agent is endowed with oneindivisible object and has preferences over all objects . An allocation of the objects is in the (strong) core if there exists no (weakly) blocking coalition . If an agent’sobject becomes more attractive for some other agents, then the agent’sallotment in the unique strong core allocation weakly improves .…

Computation of multi degree Tchebycheffian B splines

Multi-degree Tchebycheffian splines are splines with pieces drawn fromextended (complete) Tche bycheff spaces . These are a natural extension of multi-degree polynomial splines . Wepresent a practical framework to compute MDTB-splines, and provide anobject-oriented implementation in Matlab . The implementation supports the construction, differentiation, and visualization of MDTB splines whose piecesbelong to TcheByCheff spaces that are null-spaces of constant-coefficientlinear differential operators .…

Exponential Savings in Agnostic Active Learning through Abstention

We show that in pool-based active classification without assumptions on the underlying distribution, if the learner is given the power to abstain from somepredictions by paying the price marginally smaller than the average loss $1/2$ of a random guess, exponential savings in the number of label requests are possible whenever they are possible in the corresponding realizable problem .…

Open Source Concealed EEG Data Collection for Brain Computer Interfaces Real World Neural Observation Through OpenBCI Amplifiers with Around the Ear cEEGrid Electrodes

An integrated system design combines electronics components with newly designed 3D-printed partsto form an easily replicable, versatile, single-unit EEG recording system for prolonged use and easy application development . Support for alink between temporal Alpha power and flow is found, which indicates anefficient engagement of verbal-analytic reasoning with intensified flow experiences, and specifically intensified task absorption .…

Actor Critic Learning Based QoS Aware Scheduler for Reconfigurable Wireless Networks

The flexibility offered by reconfigurable wireless networks, provide new opportunities for various applications such as online AR/VR gaming, high-quality video streaming and autonomous vehicles, that desire high-bandwidth, reliable and low-latency communications . These applications come with very stringent Quality of Service (QoS) requirements and increase the burden over mobile networks .…

Expressive Neural Voice Cloning

Voice cloning is the task of learning to synthesize the voice of an unseenspeaker from a few samples . We propose a controllable voice cloning method that allows fine-grained control over various style aspects of the synthesized speech for an unseen speaker .…

BAMSim Simulator

Resource allocation is an essential design aspect in multi-protocol labelswitched and OpenFlow/SDN network infrastructures . The bandwidth allocationmodels (BAMs) are an alternative to allocate and share bandwidth among network users . BAMs have an extensive number of parameters that need to be defined andtuned to achieve an expected network performance .…

Directional Sparse Filtering using Weighted Lehmer Mean for Blind Separation of Unbalanced Speech Mixtures

In blind source separation of speech signals, the inherent imbalance in the spectrum poses a challenge for methods that rely on single-sourcedominance for the estimation of the mixing matrix . We propose an algorithmbased on the directional sparse filtering (DSF) framework that utilizes theLehmer mean with learnable weights to adaptively account for source imbalance .…

Low Power Audio Keyword Spotting using Tsetlin Machines

The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) has revolutionized human to machine interaction . Yet, the challenge of end-to-end energy efficiency, memory footprint and systemcomplexity of current Neural Network (NN) powered AI-KWS pipelines has remained present . This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM) Through significantreduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining learning efficacy .…

Computability Complexity Consistency and Controllability A Four C s Framework for cross disciplinary Ethical Algorithm Research

The ethical consequences of, constraints upon and regulation of algorithmsarguably represent the defining challenges of our age . In this work, we provide a framework to assistcross-disciplinary collaboration by presenting a Four C’s Framework covering key computational considerations researchers across such diverse fields shouldconsider when approaching these questions .…

On the Expressive Power of Homomorphism Counts

A classical result by Lov\’asz asserts that two graphs $G$ and $H$ areisomorphic if and only if they have the same left-homomorphism vector . Dell, Grohe, and Rattan showed that restrictions of the left-Homomorphism . to a class of graphs can capture several different relaxations of isomorphism, including co-spectrality(i.e.,…

Adversarially learning disentangled speech representations for robust multi factor voice conversion

Conventionalspeech representation learning methods in VC only factorize speech as speakerand content . We propose adisentangled speech representation learning framework based on adversariallearning . Four speech representations characterizing content, timbre, rhythmand pitch are extracted . The adversarial network is used to minimize the correlations between the speech representations, by randomly masking and predicting one of the representations from the others.…

Context Responsive Labeling in Augmented Reality

Augmented Reality (AR) enables mobile usersto utilize text labels, in order to provide a composite view associated withadditional information in a real-world environment . Displaying all labels for points of interest on a mobile device will lead to unwanted overlaps between information and labels .…

Symmetry Aware Reservoir Computing

The symmetry-aware RC can obtain zero error using anexponentially reduced number of artificial neurons and training data, greatlyspeeding up the time-to-result . We anticipate that generalizations of our procedure will have widespread applicability in information processing withANNs . We use our method to the parity task, a challenging benchmark problem, which highlights the benefits of symmetry matching .…

Resource Availability in the Social Cloud An Economics Perspective

This paper focuses on social cloud formation, where agents are involved in acloseness-based conditional resource sharing and build their resource sharingnetwork themselves . The objectives of this paper are: (1) to investigate theimpact of agents’ decisions of link addition and deletion on their local and global resource availability, (2) to analyze spillover effects in terms of the impact of the link addition between a pair of agents on others’ utility, (3) to study the role of agents’ closeness in determining what type of spillovereffects these agents experience in the network, and (4) to model the choices of agents that suggest with whom they want to add links in the social cloud .…