Dynamic Tolling for Inducing Socially Optimal Traffic Loads

How to design tolls that induce socially optimal traffic loads? We propose atwo-timescale discrete-time stochastic dynamics that adaptively adjusts thetoll prices on a parallel link network . We show that the loads and the tolls concentrate in a neighborhood of the fixed point, which correspondsto the socially optimal load and toll price .…

Hybrid Layers Neural Network Architectures for Modeling the Self Interference in Full Duplex Systems

Full-duplex (FD) systems have been introduced to provide high data rates forbeyond fifth-generation wireless networks . This article proposes two novel hybrid-layersneural network (NN) architectures to cancel the SI with low complexity . The key idea behindusing hybrid layers is to build an NN model, which makes use of the different layers employed in its architecture .…

Wideband and Entropy Aware Deep Soft Bit Quantization

Deep learning has been recently applied to physical layer processing indigital communication systems . We introduce a novel deep learning solution for soft bitquantization across wideband channels . Our method is trained end-to-end withquantization- and entropy-aware augmentations to the loss function .…

DNA Codes over the Ring mathbb Z _4 w mathbb Z _4

We extend the Gau map andGau distance, defined in DKBG, over all the $16$ rings$\mathcal{R}__\theta . An isometry between the codes over the rings and the analogous DNA codes is established in general . We propose family of DNA codes that satisfies reverse and reverse-complement constraints using the Reed-Muller type codes .…

Minimum ell_ 1 norm interpolators Precise asymptotics and multiple descent

An evolving line of machine learning works observe empirical evidence that interpolating estimators may not necessarily be harmful . This paper pursues theoretical understandingfor an important type of interpolator: the minimum $ell_1$-norminterpolator . We observe a curious multi-descent phenomenon; that is, the generalization risk of the minimum$\ell__1 $-norm interpolator undergoes multiple (and possibly more than two)phases of descent and ascent as one increases the model capacity .…

Fair and Efficient Allocations of Chores under Bivalued Preferences

We study the problem of fair and efficient allocation of a set of indivisible chores to agents with additive cost functions . We consider the popular fairnessnotion of envy-freeness up to one good (EF1) with the efficiency notion ofPareto-optimality (PO) While it is known that an EF1+PO allocation exists andcan be computed in pseudo-polynomial time in the case of goods, the same problem is open for chores .…

Projected Model Counting Beyond Independent Support

The past decade has witnessed a surge of interest in practical techniques forprojected model counting . Despite significant advancements, performance scaling remains the Achilles’ heel of this field . Inapplications such as verification of binarized neural networks, quantification of information flow, reliability of power grids etc.,…

Low Precision Quantization for Efficient Nearest Neighbor Search

K-Nearest Neighbor search over real-valued vector spaces (KNN) is animportant algorithmic task for information retrieval and recommendationsystems . We present a method for using reduced precision to represent vectorsthrough quantized integer values, enabling both a reduction in the memoryoverhead of indexing these vectors and faster distance computations at querytime .…

Context aware Reranking with Utility Maximization for Recommendation

Reranking rearranges items in the initial rankinglists from the previous ranking stage to better meet users’ demands . An ideal reranking algorithm should consider the counterfactual context — the position and the alignment of the items in reranked lists . CRUM significantly outperforms the state-of-the-art models in terms of both relevance-based metrics and utility-based metric metrics.…

Comparing Deep Neural Nets with UMAP Tour

A tool, UMAP Tour, is built to visually inspect and compare behavior of real-world neural network models . The method used in the visualization alsoimplies a new similarity measure between neural network layers . Using the tool and the similarity measure, we find concepts learned instate-of-the-art models and dissimilarities between them, such as GoogLeNet andResNet .…

Evaluating NISQ Devices with Quadratic Nonresidues

Algorithmsshowing a quantum advantage are often tailored precisely to what a particular NISQ does well . We prove quantum computers can find quadratic nonresidues indeterministic polynomial time . Classical version of this problem remains unsolved after hundreds of years . A success rate greater than 75% provides evidence of quantumadvantage.…

A cautionary tale on fitting decision trees to data from additive models generalization lower bounds

Decision trees are important both as interpretable models amenable to high-stakes decision-making, and as building blocks of ensemble methods such asrandom forests and gradient boosting . Their statistical properties, however,are not well understood . We prove a sharpsquared error generalization lower bound for a large class of decision tree algorithms fitted to sparse additive models with $C^1$ component functions .…

EmbRace Accelerating Sparse Communication for Distributed Training of NLP Neural Networks

EmbRace introduces Sparsity-aware Hybrid Communication, which combines AlltoAlland AllReduce to optimize communication overhead for sparse and dense datain NLP models . EmbRace achieves up to 30.66X speedupon 16 GPUs clusters among four popular distributed training baselines . Experimental results show that EmbRace can be achieved with four representative NLP model models on two high-performance GPU clusters .…

Ctrl Shift How Privacy Sentiment Changed from 2019 to 2021

People’s privacy sentiments drive changes in legislation and may influencetheir willingness to use a variety of technologies . After the onset of COVID-19, we observe significant changes in Americans’ privacy sentimentstoward government- and health-related data uses . We observe additionalchanges in the context of other national events such as the U.S.…

Turing Tumble is Turing Complete

It is shown that the toy Turing Tumble, suitably extended with an infinitelylong game board and unlimited supply of pieces, is Turing-Complete . This isachieved via direct simulation of a Turing machine . Unlike previouslyinformally presented constructions, we do not encode the finite controlinfinitely many times, we need only one trigger/ball-hopper pair, and we proveour construction correct .…

Reconfigurable Intelligent Surface Enhanced OFDM Communications via Delay Adjustable Metasurface

Reconfigurable intelligent surface (RIS) is a promising technology forestablishing spectral- and energy-efficient wireless networks . In this paper, we study RIS-enhanced orthogonal frequency division multiplexing (OFDM)communications . We introduce the delay adjustablemetasurface (DAM) relying on varactor diodes . In contrast to existingreflecting elements, each one in DAM is capable of storing and retrieving theimpinging electromagnetic waves upon dynamically controlling itselectromagnetically induced transparency (EIT) properties .…

DNA Codes over the Ring mathbb Z _4 w mathbb Z _4

We extend the Gau map andGau distance, defined in DKBG, over all the $16$ rings$\mathcal{R}__\theta . An isometry between the codes over the rings and the analogous DNA codes is established in general . We propose family of DNA codes that satisfies reverse and reverse-complement constraints using the Reed-Muller type codes .…

Affine Hermitian Grassmann Codes

The Grassmannian is an important object in Algebraic Geometry . We introduce a new class of linear codes called Affine Hermitian GrassmanCodes . These codes are the linear codes resulting from an affine part of the projective embedding of the Grassmann codes .…

Empirical Policy Optimization for n Player Markov Games

In single-agent Markov decision processes, an agent can optimize its policy based on the interaction with environment . In multi-player Markov games, the interaction is non-stationary due to the behaviors of other players . The core is to evolve one’s policy according to not just its current in-game performance, but an aggregation of its performance over history .…

Deep Learning Based Power Control for Uplink Cell Free Massive MIMO Systems

A framework for deep learning-based power control methods for max-min, max-product and max-sum-rate optimization in uplinkcell-free massive multiple-input multiple- input multiple-output (CF mMIMO) systems is proposed . Instead of using supervised learning, the proposed method relies onunsupervised learning, in which optimal power allocations are not required to be known, and thus has low training complexity .…

Small Data and Process in Data Visualization The Radical Translations Case Study

This paper uses the collaborative project Radical Translations as case study to examine some of the theoretical perspectives informing the adoption andcritique of data visualization in the digital humanities . It showcases how data visualization is used within a King’s DigitalLab project lifecycle to facilitate collaborative data exploration within the project interdisciplinary team .…

Semantics of Conjectures

This paper aims to expand and detail the notion of formal semantics of Conjectures by applying a theoretic-model approach . After a short introduction to the concepts and basics, we will start from the concept ofSimple Interpretation of RDF, applying and extending the semantic rules and conditions to fully cover the concepts .…

Ride Sharing Data Privacy An Analysis of the State of Practice

Digital services like ride sharing rely heavily on personal data . Services include a varying set of personal data and offer limited privacy-related features . Privacy concerns are a decisive factor for individuals to (not) use these services . The results show that services include a different set of data and are often limited on privacy- related features .…

Bayesian Persuasion in Sequential Trials

We consider a Bayesian persuasion or information design problem where thesender tries to persuade the receiver to take a particular action via a sequence of signals . This we model by considering multi-phase trials where the FDA determines some of the experiments .…

Ctrl Shift How Privacy Sentiment Changed from 2019 to 2021

People’s privacy sentiments drive changes in legislation and may influencetheir willingness to use a variety of technologies . After the onset of COVID-19, we observe significant changes in Americans’ privacy sentimentstoward government- and health-related data uses . We observe additionalchanges in the context of other national events such as the U.S.…

A Formalisation of Abstract Argumentation in Higher Order Logic

We present an approach for representing abstract argumentation frameworks based on an encoding into classical higher-order logic . This provides a uniform framework for computer-assisted assessment of abstract argumentations . This enables the formalanalysis and verification of meta-theoretical properties as well as theflexible generation of extensions and labellings with respect to well-known semantics .…

Joint Spatial Division and Coaxial Multiplexing for Downlink Multi User OAM Wireless Backhaul

Orbital angular momentum (OAM) at radio frequency (RF) provides a novel approach of multiplexing a set of orthogonal modes on the same frequency channel to achieve high spectral efficiencies (SEs) At last, the proposed methods are extended to the downlink MU-OAM-MIMO wireless backhaul system equipped with uniform concentric circular arrays (UCCAs) for which much higher spectral efficiency (SE) and energy efficiency (EE) can be achieved .…

Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E Commerce

In e-commerce, the watchlist enables users to track items over time and hasemerged as a primary feature, playing an important role in users’ shopping journey . Watchlist items typically have multiple attributes whose values maychange over time (e.g., price, quantity) Since many users accumulate dozens of items on their watchlist, and since shopping intents change over time,recommending the top watchlist items in a given context can be valuable .…

Learning Realtime One Counter Automata

Ouralgorithm uses membership and equivalence queries as in Angluin’s L* algorithm . In a partialequivalence query, we ask the teacher whether the language of a givenfinite-state automaton coincides with a counter-bounded subset of the targetlanguage . We evaluate an implementation of our algorithm on a number of randombenchmarks .…

DroneStick Flying Joystick as a Novel Type of Interface

DroneStick is a novel hands-free method for smooth interaction between a human and a robotic system via one of its agents . A flying joystick(DroneStick) is composed of a flying drone and coiled wire with a vibration motor . A potential application can enhance an automated `lastmile’ delivery when a recipient needs to guide a delivery drone/robot gently to a spot where a parcel has to be dropped .…

Don t Judge Me by My Face An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews

Adversarial methods have been proven to effectively remove sensitive information from the latent representation of neural networks without the need to collect any sensitive variable . This is the first application of adversarial techniques for obtaining a multimodal fair representation in the context of video job interviews .…

On line Optimal Ranging Sensor Deployment for Robotic Exploration

The approach is general for any class of mobile system, we run simulations and experiments with indoor drones . We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows . We developed a genetic algorithm that minimizes the deployment of newanchors, saving energy and resources on the mobile robot and maximizing the mission .…

Structured vector fitting framework for mechanical systems

In this paper, we develop a structure-preserving formulation of the data-driven vector fitting algorithm for the case of modally damped mechanical systems . We propose two possible structuredextensions of the barycentric formula of system transfer functions . Integrating these new forms within the classical vector fitting algorithms leads to theformulation of two new algorithms .…

A Primer on the Statistical Relation between Wireless Ultra Reliability and Location Estimation

This letter statistically characterizes the impact of location estimationuncertainty in the wireless communication reliability . The reliability – characterized by how likely the outage probabilityis to be above a target threshold – can be sensitive to location errors . We highlight the difficulty of choosing a rate that both meets targetreliability and accounts for the location uncertainty, and that the most directsolutions suffer from being too conservative .…

Uncertainty aware Topic Modeling Visualization

Topic modeling is a state-of-the-art technique for analyzing text corpora . It uses a statistical model, most commonly Latent Dirichlet Allocation (LDA) to discover abstract topics that occur in the document collection . The LDA-based topic modeling procedure is based on a randomly selected initialconfiguration .…

The search of Type I codes

A self-dual binary linear code is called Type I code if it has singly-evencodewords, i.e.~it has codewords with weight divisible by $2.$ The purpose of this paper is to investigate interesting properties of Type I codes . Further, we build up a computer-based code-searching program .…