## Philosophical Specification of Empathetic Ethical Artificial Intelligence

An ethical AI must be capable of inferring unspoken rules, interpreting nuance and context, possess and be able to infer intent, and explain not just its actions but its intent . It can learn what is meant by a sentence and infer the intent of others in terms of its own experiences .…

## Shedding some light on Light Up with Artificial Intelligence

The Light-Up puzzle, also known as the AKARI puzzle, has never been solved using modern artificial intelligence (AI) methods . This project is an effort to apply new AI techniques for solving the Light-up puzzle faster and more computationallyefficient . The algorithms explored for producing optimal solutions include hillclimbing, simulated annealing, feed-forward neural network (FNN), and CNN, and an evolutionary theory algorithm .…

## Fast Low Rank Tensor Decomposition by Ridge Leverage Score Sampling

Low-rank tensor decomposition generalizes low-rank matrix approximation and is a powerful technique for discovering low-dimensional structure in high-dimensional data . We study Tucker decompositions and usetools from randomized numerical linear algebra called ridge leverage scores toaccelerate the core tensor update step in the widely-used alternating leastsquares (ALS) algorithm .…

## Specifying a Game Theoretic Extensive Form as an Abstract 5 ary Relation

This paper specifies an extensive form as a 5-ary relation (i.e. set ofquintuples) which satisfies certain abstract axioms . Each quintuple is understood to list a player, a situation (e.g. information set), a decisionnode, a decision node, an action, and a successor node .…

## Equidistant Linear Codes in Projective Spaces

Linear codes in projective space $mathbb{P}_q(n)$ were first considered by Braun,Etzion and Vardy . We establish that the normalizedminimum distance of a linear code is maximum if and only if it is equidistant . We prove that the upper bound on the size of such class of linear codes is $2^n$ when $q=2$ as conjectured by Braun et al.…

## Frost Benchmarking and Exploring Data Matching Results

“Bad” data has a direct impact on 88% of companies, with the average company losing 12% of its revenue due to it . Duplicates – multiple but different representations of the same real-world entities – are among the main reasons for poor data quality .…

## Evaluation of In Person Counseling Strategies To Develop Physical Activity Chatbot for Women

Artificial intelligence chatbots are the vanguard in technology-based intervention to change people’s behavior . To develop intervention chatbots, the first step is to understand natural language conversation strategies in humanconversation . This work lays the foundation for developing a personalized physical activity intervention bot .…

## Super Resolution on the Two Dimensional Unit Sphere

We study the problem of recovering an atomic measure on the unit 2-sphere $\mathbb{S}^2$ given finitely many moments with respect to spherical harmonics . We construct a dual certificate using a kernel given in an explicit form and make a concrete analysis of the interpolation problem .…

## Lower Bounds for Maximally Recoverable Tensor Code and Higher Order MDS Codes

Maximally Recoverable (MR) TensorCodes, introduced by Gopalan et al., are tensor codes which can correct everyerasure pattern that is theoretically possible to correct . Tensor codes are useful in distributed storage because a single erasure can be correctedquickly either by reading its row or column .…

## SAGE A Split Architecture Methodology for Efficient End to End Autonomous Vehicle Control

Autonomous vehicles require large Deep-Learning (DL) models and powerful hardware platforms to operate reliably in real-time . SAGE: a methodology for selectively offloading the key energy-consuming modules of DL architectures to the cloud to optimize edge energy usage while meeting latency constraints .…

## Establishing Digital Recognition and Identification of Microscopic Objects for Implementation of Artificial Intelligence AI Guided Microassembly

Many current micro-assembly methods are serial in nature, resulting in unfeasibly low throughput . Alternatively, parallel self-assembly ordirected-assembly techniques can be employed by utilizing forces dominant atthe micro and nano scales such as electro-kinetic, thermal, and capillaryforces . However, these forces are governed by complex equations and often act on microparts simultaneously and competitively, making modeling and simulation difficult .…

## Incentive Compatible Mechanism for Influential Agent Selection

In a self-interested setting, agents may strategically hide some connections to make themselves seem to be more important . In this paper, we study the incentive compatible (IC) selectionmechanism to prevent such manipulations . We propose the Geometric Mechanism, which selects an agent with at least 1/2 of the optimal progeny in expectation under the properties of incentive compatibility and fairness .…

## High performance low complexity error pattern generation for ORBGRAND decoding

Guessing Random Additive Noise Decoding (GRAND) is a recently proposed method searching for the error pattern applied to the transmittedcodeword . We propose an improved error pattern schedule that can improve the performance ofORBGRAND of 0.5dB at a block error rate (BLER) of $10^{-5}$, with increasinggains as the BLER decreases .…

## LES3 Learning based Exact Set Similarity Search

Set similarity search is a problem of central interest to a wide variety of applications such as data cleaning and web search . Past approaches on setsimilarity search utilize either heavy indexing structures, incurring largesearch costs or indexes that produce large candidate sets .…

## Linear Polytree Structural Equation Models Structural Learning and Inverse Correlation Estimation

We are interested in learning the directed acyclic graph (DAG) when data are generated from a linear structural equation model (SEM) and thecausal structure can be characterized by a polytree . We also study the errorrate for the estimation of the inverse correlation matrix under such models .…

## Towards an understanding of how humans perceive stiffness during bimanual exploration

In this paper, an experimental testbed and associated psychophysical paradigmare presented for understanding how people discriminate torsional stiffness . Participants explored virtual virtualtorsion springs by rotating their forearms . The discrimination results will inform futureinvestigation into understanding how stiffness percepts vary .…

## MFGNet Dynamic Modality Aware Filter Generation for RGB T Tracking

MFGNet aims to boost the message communication between visible and thermaldata by adaptively adjusting the convolutional kernels for various input images . To address issues caused by heavy occlusion, fast motion, and out-of-view, we propose to conduct a joint local and global search byexploiting a new direction-aware target-driven attention mechanism .…

## Pre Clustering Point Clouds of Crop Fields Using Scalable Methods

In order to apply the recent successes of automated plant phenotyping and machine learning on a large scale, efficient and general algorithms must be bedesigned to intelligently split crop fields into small, yet actionable,portions that can then be processed by more complex algorithms .…

## CURE Enabling RF Energy Harvesting using Cell Free Massive MIMO UAVs Assisted by RIS

The ever-evolving internet of things (IoT) has led to the growth of numerous wireless sensors, communicating through the internet infrastructure . For extending the lifetime of thesesensors, radio frequency energy harvesting (RFEH) technology has proved to be promising . In this paper, we propose CURE, a novel framework for RFEH that combines the benefits of cell-free massive MIMO (CFmMIMO), unmannedaerial vehicles (UAVs), and reconfigurable intelligent surfaces (RISs) toprovide seamless energy harvesting to IoT devices .…

## Specifying a Game Theoretic Extensive Form as an Abstract 5 ary Relation

This paper specifies an extensive form as a 5-ary relation (i.e. set ofquintuples) which satisfies certain abstract axioms . Each quintuple is understood to list a player, a situation (e.g. information set), a decisionnode, a decision node, an action, and a successor node .…

## Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference

The widely used domain invariant feature learning (IFL) methods relies on aligning the marginal concept shift w.r.t. $p(x|y)$ and the marginal label shift . In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training .…

## Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference

The widely used domain invariant feature learning (IFL) methods relies on aligning the marginal concept shift w.r.t. $p(x|y)$ and the marginal label shift . In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training .…

## To Ship or Not to Ship An Extensive Evaluation of Automatic Metrics for Machine Translation

Automatic metrics are commonly used as the exclusive tool for declaring thesuperiority of one machine translation system’s quality over another . We investigate which metrics have the highest accuracy to makesystem-level quality rankings for pairs of systems . We show that the sole use of BLEUnegatively affected the past development of improved models.…

## Impacts Towards a comprehensive assessment of the book impact by integrating multiple evaluation sources

The surge in the number of books published makes the manual evaluation methods difficult to efficiently evaluate books . The use of books’ citationsand alternative evaluation metrics can assist manual evaluation and reduce the cost of evaluation . However, relying on a single resource for book assessment may lead to the risk that theevaluation results cannot be obtained due to the lack of the evaluation data, especially for newly published books .…

## On the Stability Regions of Coded Poisson Receivers with Multiple Classes of Users and Receivers

Motivated by the need to provide differentiated quality-of-service (QoS) ingrant-free uplink transmissions in 5G networks and beyond, we extend theprobabilistic analysis of coded Poisson receivers (CPR) to the setting with multiple classes of users and receivers . For such a CPR system, we prove (undercertain technical conditions) that there is a region, called the stabilityregion in this paper .…

## Continuity estimates for Riesz potentials on polygonal boundaries

Riesz potentials are well known objects of study in the theory of singularintegrals . They have been the subject of recent interest from thenumerical analysis community due to their connections with fractional Laplaceproblems and proposed use in certain domain decomposition methods .…

## What Makes Sound Event Localization and Detection Difficult Insights from Error Analysis

Sound event localization and detection (SELD) aims to unify the tasks of sound event detection and direction-of-arrivalestimation . SELD inherits the challenges of both tasks, such as noise, reverberation, interference, polyphony, and non-stationarity of soundsources . Experimental results indicate polyphony as the main challenge in SELD, due to the difficulty in detecting all sound events of interest .…

## A convergent finite element algorithm for mean curvature flow in higher codimension

Optimal-order uniform-in-time $H^1$-norm error estimates are given for semi-and full discretizations of mean curvature flow of surfaces in arbitrarily high codimension . This numerical method admits a convergence analysis in the case of finiteelements of polynomial degree at least two and backward difference formulae oforders two to five .…

## Codeathon Activity A Design Prototype for Real World Problems

Avirtual codeathon activity, as part of this learning scheme, was conducted for180 undergraduate students to focus on analysis and design of solutions to real-world problems in the Covid-19 pandemic situation . Activity-based learning helps students to learn through participation, AvVirtual Codeathon activity was conducted by students .…

## Multi Stream Transformers

Transformer-based encoder-decoder models produce a fused token-wiserepresentation after every encoder layer . We investigate the effects of allowing the encoder to preserve and explore alternative hypotheses, combined at the end of the encoding process . We design and examine a $\textit{Multi-stream Transformer}$ architecture and find that splitting theTransformer encoder into multiple encoder streams and allowing the model to merge multiple representational hypotheses improves performance .…

## Target Oriented Fine tuning for Zero Resource Named Entity Recognition

Zero-resource named entity recognition (NER) severely suffers from datascarcity in a specific domain or language . Most studies on zero-resource NERtransfer knowledge from various data by fine-tuning on different auxiliary tasks . In this paper, we tackle the problem by transferring knowledge from three aspects, i.e.,…

## A local approach to parameter space reduction for regression and classification tasks

New method called localactive subspaces (LAS) combines clustering techniques with a more efficient dimension reduction in the parameter space for the design of accurate response surfaces . The drawback of this approach is the possible scarcity of data in some applications, but in those, where a quantityof data, moderately abundant is available, partitioned or localstudies are beneficial .…