Transfer Learning for Human & AI

Theory and simulations show that when the network and infection parametersare conducive to strong community structure, our proposed adaptive,graph-aware algorithm outperforms the baseline binary splitting algorithm, and is even order-optimal in certain parameter regimes . Authors: We derive novelinformation-theoretic lower bounds which highlight the fundamental limits of adaptive group testing in our networked setting.…

This document gives a set of recommendations to build and manipulate the datasets used to develop and/or validate machine learning models such as deepneural networks . This is a work in progress as good practicesevolve along with our understanding of machine learning .…

An iterative randomness extraction algorithm which generalized the VonNeumann’s extraction algorithm is detailed, analyzed and implemented instandard C++ . Given a sequence of independently and identically distributedbiased Bernoulli random variables, to extract randomness from theaforementioned sequence pertains to produce a new sequence of individually andidentically distributed unbiased random variables .…

This paper investigates the classical integer least-squares problem whichestimates integer signals from linear models . Problem is NP-hard and oftenarises in diverse applications such as signal processing, bioinformatics, communications and machine learning . We propose a generalhyper-accelerated tree search (HATS) algorithm by employing a deep neuralnetwork to estimate the optimal heuristic for the underlying simplified memory-bounded A* algorithm .…

SimpDOM outperforms the state-of-the-art (SOTA) method by 1.44% on the F1score. We also find that utilizing knowledge from a different vertical(cross-vertical extraction) is surprisingly useful and helps beat the SOTA by afurther 1.37% . The method is transferable and efficient to efficiently retrieve useful context for each node by leveraging the structure of the HTML DOM tree structure .…

The setlist identification (SLI) task addresses a music recognition use casewhere the goal is to retrieve the metadata and timestamps for all the tracks played in live music events . The approach can identify68% of the annotated segments, with values ranging from 35% to 77% based on the genre .…

Deep neural networks are easily misled by adversarial examples . How to evaluatethe adversarial robustness effectively is important for the realistic deployment of deep models . We hope theseanalyses and results will help the community to develop more powerful defenses .…

In this paper we present an efficient reachability oracle under single-edgeor single-vertex failures for planar directed graphs . We show that a planar digraph $G$ can be preprocessed in $O(n\log^2{n}/\log\log{n)$time . To the best of our knowledge, this is the first datastructure for .…

Computational inference of dated evolutionary histories relies upon varioushypotheses about RNA, DNA, and protein sequence mutation rates . Using mutationrates to infer these dated histories is referred to as molecular clockassumption . Coalescent theory is a popular class of evolutionary models thatimplements the molecular clock hypothesis to facilitate computational inferenceof dated phylogenies .…

In this work, we consider the task of faithfully simulating a distributedquantum measurement and function computation, and demonstrate a new achievableinformation-theoretic rate-region . For this, we develop the technique ofrandomly generating structured POVMs using algebraic codes . We develop a Pruning Traceinequality which is a tighter version of the known operator Markov inequality .…

Merging beliefs depends on the relative reliability of their sources . Whenunknown, assuming equal reliability is unwarranted . Alternatively, one source is completely reliable,but which one is unknown . These two cases motivate two existing forms of merging: maxcons-based merging and arbitration .…

A novel approach on parallelization of Newton-Raphson power flow for many calculations on CPU and with GPU-acceleration is proposed . The result shows a speed-up of over x100 comparing to the open-source tool pandapower, when performing repetitive power flows of system with admittance matrix of the same sparsity pattern on both CPU and GPU .…

We use the SYK family of models with $N$ Majorana fermions to study the complexity of time evolution . Initially, the shortest geodesic followsthe time evolution trajectory, and hence complexity grows linearly in time . Westudy how this linear growth is eventually truncated by the appearance andaccumulation of conjugate points, which signal the presence of shortergeodesics intersecting time evolution trajectories .…

GridRange class of data structure problems over integer arrays in one or more dimensions . These problems allow range updates (such as filling all cells in arange with a constant) and queries . We show that no truly subquadratic time algorithm can support certain pairsof these updates simultaneously without falsifying several popular conjectures .…

A regular path query (RPQ) is a regular expression that returns all nodepairs (u, v) from a graph database that are connected by an arbitrary path labelled with a word from L(q) A main insight isthat we can achieve optimal (or near optimal) algorithms with the PG-approach, but the delay for enumeration is rather high (linear in the database) We explore three successful approaches towards enumeration with sub-linear delay:super-linear preprocessing, approximations of the solution sets, and restricted classes of RPQs .…

Polynomial multiplication is known to have quasi-linear complexity in both dense and sparse cases . Yet no truly linear algorithm has been given in any case for the problem, and it is not clear whether it is even possible . Thisleaves room for a better algorithm for the simpler problem of verifying apolynomial product .…

Highway is a new consensus protocol that is safe and live in theclassical partially synchronous BFT model . Block finality in Highway is not binary but is expressed by fraction of nodes that would need to break the protocol rules in order for a block to be reverted .…

Recently, federated learning (FL) has been subject to both security and privacy attacks posing a dilemmatic challenge on the underlying algorithmicdesigns . FLGUARD is a novel in-depth defense for FL that tackles this challenge . It applies a multilayered defense by using a Model Filtering layer to detect and reject malicious model updates and a Poison Elimination layer to eliminate any effect of a remaining weak manipulation .…

We propose a new ‘Bi-Reduced Space’ approach to solving 3D Variational DataAssimilation using Convolutional Autoencoders . We prove that our approach hasthe same solution as previous methods but has significantly lower computationalcomplexity . We reduce the computational cost without affecting data assimilation accuracy .…

The security pitfalls of IoT devices have made it easy for hackers to take over IoT devices and use them for malicious activities like botnet attacks . Botnet attacks are not only catastrophic forIoT device users but also for the rest of the world .…

The honeypot introduced in this work is able to handle commands in anon-standard way by blocking them or replying with an insult to the attacker . The findings show that attackers react to insults and blockedcommands in different ways, ranging from ignoring to sending insultsthemselves .…

Advanced Persistent Threats (APTs) are sophisticated multi-step attacks,planned and executed by skilled adversaries . Intrusion Detection Systems (IDSs) and User and EntityBehavior Analytics (UEBA) are commonly employed to aid a security analyst inthe detection of APTs . In this paper, we provide, up to our knowledge, the first study and implementation of anend-to-end AI-assisted architecture for detecting APTs — RANK .…

We want in this article to show the usefulness of Quantum Turing Machine in a high-level didactic context as well as in theoretical studies . We use QTM to show its equivalence with quantum circuit model for Deutsch and Deutsch-Jozsa algorithms .…

It has been shown in the literature that marijuana use is associated with changes in brain network connectivity . We propose large-scale Extended GrangerCausality (lsXGC) and investigate whether it can capture such changes usingresting-state fMRI . We investigate whether this model can serve as abiomarker for classifying marijuana users from typical controls using 126 adults with a childhood diagnosis of ADHD from the Addiction ConnectomePreprocessed Initiative (ACPI) database .…

We study FO+ a fragment of first-order logic on finite words . We show that there is a FO-definablelanguage that is monotone in monadic predicates but not definable in FO+. This provides a simple proof that Lyndon’s preservation theorem fails on finitestructures .…

Haptic guidance (HG) improves users’ task performancethrough physical interaction between robots and users . We propose implementation methods for each HG type using deeplearning-based approaches . UPHG induces better subjective evaluations, such as naturalness and comfort, than OAHG . CombHG that we proposed furtherdecreases disagreement between the user intention and HG, without reducing the objective and subjective scores.…

Nanoscale wireless networks are expected to revolutionize a variety of domains, with significant advances conceivable in in-body healthcare . Inhealthcare, these nanonetworks will consist of energy-harvesting nanodevices flowing through the bloodstream, taking actions at certain locations, communicating results to more powerful Body Area Network (BAN) nodes .…

Triplet Matching Network (TMN) finds the appropriate pairs for a given query concept . TMN consists of one primal scorer and multiple auxiliary scorers . An innovative channel-wisegating mechanism that retains task-specific information in concept representations is introduced to further boost model performance .…

To support large-scale deployment of unmanned aerial vehicles (UAVs) infuture, a new wireless communication paradigm, namely, cellular-connected UAV, has recently received an upsurge of interests in both academia and industry . The highaltitude of UAVs results in more frequent line-of-sight (LoS) channels with both their associated and non-associated BSs in a much wider area, which causes aerial-ground interference .…

This paper investigates the impacts of Inter-Channel Interference (ICI)effects on a shallow underwater acoustic (UWA) orthogonal frequency-divisionmultiplexing (OFDM) communication system . The channel capacity of aUWA system is severely suffered by the ICI effect . Numerical results show that the various factors of a UWA-OFDM system as subcarriers, bandwidth, andOFDM symbols affect the channel capacity under the different Dopplerfrequencies .…

SF-QA: simple and fair evaluation framework for open-domain QA system . The proposed evaluation framework is publicly available and anyone can contribute to the code and evaluations . The proposal makes the task itself easily accessible and reproducible to research groups without enough computing resources without enough resources to build the full system .…

Media-based modulation (MBM) is a novel modulation technique that can improve the spectral efficiency of existing wireless systems . In MBM, multipleradio frequency (RF) mirrors are placed near the transmit antenna(s) and are switched ON/OFF to create different channel fade realizations .…

Single-shot Policy Explanation for Augmenting Rewards (SPEAR) is an algorithm that uses semantic explanations derivedfrom combinations of planning predicates to augment agents’ reward functions . SPEAR makes substantial improvements over the current state-of-the-art in terms of runtime and addressable problem size, according to the authors .…

Developing human-like conversational agents is a prime area in HCI research and subsumes many tasks . We propose using semi-supervised techniques to automate the process of identifying backchannels, thereby easing the annotation process . We compared the backchannelprediction models trained on (a) manually-annotated and (b) semi-Supervisedlabels .…

This paper introduces neuroevolution for solving differential equations . Neuroevolution carries out a parallelexploration of diverse solutions with the goal of circumventing local optima . It could potentially find more accurate solutions with better optimized neuralnetworks. However, neuroevolutions can be slow, raising tractability issues in practice.…

We present a deep learning based joint source channel coding (JSCC) schemefor wireless image transmission over multipath fading channels with non-linearsignal clipping . The proposed encoder and decoder use convolutional neuralnetworks (CNN) and map the source images to complex-valued basebandsamples for orthogonal frequency division multiplexing (OFDM) transmission .…

VirtualFederated Science Instrument Environment (VFSIE) emulates the federation using containers and hosts connected over an emulated network . VFSIE is a digital twin of the physical infrastructure, called the Virtual Federation System . Weillustrate its use in a case study involving Jupiter Notebook computations and instrument control .…

Planning collision-free paths for multi-robot systems (MRS) is a challenging problem because of the safety and efficiency constraints required for real-world solutions . While mostcentrally-planned algorithms use static prioritization, a dynamicprioritization algorithm, PD* is proposed that employs a novel metric, calledfreedom index, to decide the priority order of the robots at each time step .…

Under the federated learning paradigm, a set of nodes can cooperatively train a machine learning model with the help of a centralized server . Such a server is tasked with assigning a weight to the information received from each node, and often also to drop too-slow nodes from the learning process .…

The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality . The two tracks in this challenge will focus on real-time denoising for (i) wide band, and (ii) fullband scenarios .…

DeepIA is a deep neural network (DNN) framework for enabling fast and reliable initial access for AI-driven beyond 5G and 6G millimeter (mmWave) networks . DeepIA reduces the beam sweep time compared to a conventionalexhaustive search-based IA process by utilizing only a subset of the available beams .…

We present a general, category independent approach to Logics ofFirst-Order Constraints (LFOC) Traditional First-Order Logic, DescriptionLogic and the sketch framework are discussed as examples . We use the concept ofinstitution [Diaconescu08,GoguenBurstall92] as a guideline to describe LFOC’s . The main result states that any choice of the six parameters, we are going to describe, gives us a corresponding “institution of constraints” at hand .…

The task of identifying emotions from a given music track has been an activepursuit in the Music Information Retrieval (MIR) community for years . Musicemotion recognition has typically relied on acoustic features, social tags, and social tags to identify and classify music emotions .…

Ultra-reliable, low-latency communication (URLLC) represents a new focus in 5G-and-beyond networks . It is expected to enable mission-critical sensing and control as well as AR/VR applications . We propose a real-time scheduling algorithm based on local-deadline-partition (LDP) The LDP algorithm is suitable for distributed implementation, and it ensures probabilistic per-packet real time guarantees formulti-cell, multi-channel networks with general deadline constraints .…

Speaker counting is the task of estimating the number of people that are simultaneously speaking in an audio recording . In this work, we show that, for agiven frame, there is an optimal position in the input sequence for best prediction accuracy .…

An end-to-end (E2E) speaker-attributed automatic speech recognition (SA-ASR) model was proposed recently to jointly perform speaker counting, speechrecognition and speaker identification . However, the E2E model is susceptible to the mismatch between the training and testing conditions . The proposed method significantlyimproves SA-WER especially for long-form multi-talker recordings, especially for multi-talkinger recordings .…

The transformation of graphs and graph-like structures is ubiquitous incomputer science . When a system is described by graph-transformation rules, it is often desirable that the rules are both terminating and confluent . However, there are application scenarios where rules are not globallyconfluent but confluent on a subclass of graphs that are of interest .…

Non-orthogonal multiple access (NOMA) and millimeter wave (mmWave) are twokey enabling technologies for the fifth-generation (5G) mobile networks and beyond . Previous work on about mmWave NOMA mostlydepends on full knowledge of channel state information (CSI) which is extremelydifficult to obtain accurately in mmWave communication systems .…

A key challenge in robotic food manipulation is modeling the materialproperties of diverse and deformable food items . We propose using a multimodalsensory approach to interact and play with food that facilitates the ability to distinguish these properties across food items.…

This paper considers a cooperative cognitive radio network with two primary users (PUs) and two secondary users (SUs) that enables two-way communication . SUs are able to realize their communications over the licensed spectrum while extending relay assistance to the PUs .…