Transfer Learning for Human & AI

The roots of a monic polynomial expressed in a Chebyshev basis are known to be the eigenvalues of the so-called colleague matrix . In this manuscript, we describe an $O(n^2)$ explicitstructured QR algorithm for colleague matrices . We prove that it is componentwise backward stable, in the sense that the backward error in the colleague matrix can be represented as relative perturbations to its components .…

In this article, we consider computing expectations w.r.t. probabilitymeasures which are subject to discretization error . Examples include partiallyobserved diffusion processes or inverse problems, where one may have todiscretize time and/or space, in order to practically work with the probabilityof interest .…

Results on unconditional convergence in the Maximum norm for ADI-typemethods are quite difficult to get, mainly when thenumber of space dimensions $m$ is greater than two . Such a result is obtained under quite general conditions on the PDE problem in case that Dirichlet boundary conditions are imposed .…

Word segmentation and part-of-speech tagging are two critical preliminary steps for downstream tasks in Vietnamese natural language processing . In reality, people tend to consider also the phrase boundary when performing wordsegmentation and . part of speech tagging rather than solely process word by word from left to right .…

As novel applications spring up in future network scenarios, the requirements on network service capabilities for differentiated services or burst servicesare diverse . Migrating computing tasks to the edge and cloudfor computing requires a comprehensive consideration of energy consumption, bandwidth, and delay .…

Moral foundations theory helps understand differences in morality across cultures . In this paper, we propose a model to predict moral foundations (MF) from social media trending topics . We also investigate whether differences inMF influence emotional traits .…

Domain Identification plays a significant role in Machine Translation, Text Summarization, Question Answering,Information Extraction, and Sentiment Analysis . System got 69.9% of the F1score on the test dataset and 90.01% on the validation set . This architecture was used and evaluated in the context of the ICONshared task TechDOfication 2020 (task h) Thematic keywords give a compressedrepresentation of the text, and usually, Domain Identification is used in machine translation .…

We consider the approximation of manifold-valued functions by embedding them into a higher dimensional space, applying a vector-valuedapproximation operator and projecting the resulting vector back to themanifold . We provide explicitconstants that depend on the reach of the embedded manifold .…

A Boolean constraint satisfaction problem (CSP) is amaximization problem specified by a constraint $f:\{-1,1\}^k\to\{0,1$ The goal is to compute the maximum number of constraints that can be satisfied by a Boolean assignment to the $n$~variables . In this work we completely characterize the approximability of all BooleanCSPs in the streaming model .…

Machine learning (ML) has been used to develop increasingly accurate link quality estimators for wireless networks . We propose a newtree-based link quality classifier that meets high performance and fairlyclassifies the minority class and, at the same time, incurs low training cost .…

Inertia of the power grids is declining, which results in a faster drop insystem frequency in case of load-generation imbalance . Power grids with renewables are moresusceptible to FRO attacks and the inertia of synchronous generators plays acritical role in reducing the success of FRo attacks in power grids .…

False Data Injection (FDI) attacks against powersystem state estimation are agrowing concern for operators . The attack is based on a combinestopology learning technique, based only on branch and buspowerflows, and attacker-side pseudo-residual assessment to performstealthy FDIattacks with high confidence .…

Stifle joint issues are a major cause of lameness in dogs and it can be asignificant marker for various forms of diseases or injuries . A known TibialPlateau Angle (TPA) helps in the reduction of the diagnosis time of the cause .…

Bitcoin and Ethereum transactions present one of the largest real-world complex networks that are publicly available for study . Preference attachment continues to be a key factor in the evolution of both the Bitcoin and . Ethereum, the second most important cryptocurrency, continues to evolve, authors say .…

This thesis proposes techniques aiming to make blockchain technologies andsmart contract platforms practical by improving their scalability, latency, andprivacy . This thesis starts by presenting the design and implementation ofChainspace, a distributed ledger that supports user defined smart contracts and executes user-supplied transactions .…

We develop a resource theory of symmetric distinguishability . We study the resource theory for two different classes of free operations . The optimal rate of converting oneelementary source to another is equal to the ratio of their quantum Chernoff divergences .…

Stringent constraints on both reliability and latency must be guaranteed inultra-reliable low-latency communication (URLLC) To fulfill these constraints with computationally constrained receivers, optimal transmission parameters need to be studied in detail . For this purpose, a multi-objective optimization problem (MOOP) is formulated .…

We study the problem of modeling a binary operation that satisfies somealgebraic requirements . We first construct a neural network architecture for Abelian group operations and derive a universal approximation property . Then,we extend it to Abelian semigroup operations using the characterization ofassociative symmetric polynomials .…

Standard deepneural networks typically yield uncalibrated predictions, which can be betransformed into confidence scores using post-hoc calibration methods . We address the problem of uncertainty calibration and introduce a novel method, Parametrized Temperature Scaling (PTS) We show that our novel accuracy-preserving approach consistently outperforms existing algorithms across a large number of modelarchitectures, datasets and metrics .…

Post-release user feedback plays an integral role in improving software quality and informing new features . Confidentiality and privacy concernsvaried in severity, and were most prevalent over Jelly Bean releases . Community users also expressed divergent preferences for new security features, ranging from more relaxed to very strict .…

The rank $r$ rigidity of $M$ is the smallest number of entries which one must change to make its rank atmost $r$. The $N \times N$ Walsh-Hadamard transform has a linear circuit of size $O(d \cdot N^{1+ 0.96/d) The new rigidity upper bound, showing that the following classes of matrices are not rigid enough to prove circuit lower bounds using Valiant’s approach, generalizes recent results on non-rigidity, using a simpler approach which avoids needing the polynomial method .…

Locally Differentially Private (LDP) Reports are commonly used for collection of statistics and machine learning in the federated setting . LDP reports are known to have relatively little information about the user’s data due to randomization . Several schemes are known that exploit this fact to design low-communication versions of LDP algorithms but all of them do so at the expense of a significant loss in utility .…

We propose amulti-task inverse reinforcement learning (IRL) algorithm, called \emph{inversetemporal difference learning} (ITD) that learns shared state features and per-agent successor features . We further show how to seamlesslyintegrate ITD with learning from online environment interactions, arriving at anovel algorithm for reinforcement learning with demonstrations, called $\Psi\Phi$-learning (pronounced `Sci-Fi’) We provide empirical evidence for the effectiveness of this method for improving RL, IRL,imitation, and few-shot transfer, and we derive worst-case bounds for its performance in zero-shot transfers to new tasks .…

This work deals with error models for trident quaternion framework proposed in companion paper “A Trident Quaternion Framework for Inertial-basedNavigation Part I: Motion Representation and Computation” It further uses them to investigate the static and in-motion alignment for land vehicles .…

Constraint-based recommenders support users in the identification of items fitting their wishes and needs . Example domains are financialservices and electronic equipment . In this paper we show how divide-and-conquerbased (direct) diagnosis algorithms (no conflict detection is needed) can be used in constraint-based recommendation scenarios .…

Each statement in Wikipediashould be referenced . In this paper, we explore the creation and collection of references for new Wikipedia articles from an editors’ perspective . We map out the workflow of editors when creating a new article .…

Word embedding learning methods require a large number of occurrences of aword to accurately learn its embedding . Out-of-vocabulary (OOV) words do not appear in the training corpus emerge frequently in the smallerdownstream data . We propose the use of Leap, ameta-learning algorithm which leverages the entire trajectory of the learning process instead of just the beginning and the end points .…

We prove large (and moderate) deviations for a class of linear combinationsof spacings generated by i.i.d. exponentially distributed random variables . Weallow a wide class of coefficients which can be expressed in terms of coefficients . We generalize some recent results by Giuliano et al.…

Using task-specific pre-training and leveraging cross-lingual transfer are two of the most popular ways to handle code-switched data . In this paper, we aim to compare the effects of both for the task of sentiment analysis . We work with two Dravidian Code-Switched languages – Tamil-Engish and Malayalam-Englishand four different BERT based models .…

The evolution of language has been a hotly debated subject with contradictinghypotheses and unreliable claims . Drawing from signalling games, dynamicpopulation mechanics, machine learning and algebraic topology, we present amethod for detecting evolutionary patterns in a sociological model of languageevolution .…

With the popularity of online access in virtual reality (VR) devices, it will become important to investigate exclusive and interactive CAPTCHA designs for VR devices . In this paper, we present four traditional two-dimensional (2D) CAPTCHAs in VR . Then, based on the three-dimensional interactioncharacteristics of VR devices, we propose two vrCAPTCHA design prototypes .…

AutoAI for Time Series Forecasting (AutoAI-TS) provides users with a zeroconfiguration (zero-conf ) system to efficiently train, optimize and choose best forecasting model among various classes of models for the given dataset . Automatically providing a good set of models to users for a givendataset saves both time and effort from using trial-and-error approaches .…

The false data injection (FDI) attack is a crucial form of cyber-physical security problems facing cyber power systems . There is noresearch revealing the problem of FDI attacks facing voltage source converterbased high voltage direct current transmission (VSC-HVDC) systems . And finally, the modified IEEE-14 bus system is used to demonstrate that attackers are capable of disrupting the operation security of converter stations in VSC- HVDC systems by FDI attack strategies .…

Mitigating bias in machine learning systems requires refining our understanding of bias propagation pathways . A metric formeasuring bias amplification was introduced in the seminal work by Zhao et al. We introduceand analyze a new, decoupled metric for measuring bias amplification,$\text{BiasAmp}_{\rightarrow}$ (Directional Bias Amplification) We provide suggestions about its measurement by cautioning against predicting sensitive attributes, encouraging the use ofconfidence intervals due to fluctuations in the fairness of models across runs,and discussing the limitations of what this metric captures .…

Multigrid methods are one of the most efficient techniques for solving linearsystems arising from Partial Differential Equations (PDEs) and graph Laplacians . The CNNs are trained on small-scale problems from a given type of PDEs based on a supervised lossfunction derived from multigrid convergence theories .…

Lungs in the pneumothorax state during surgery have a large volumechange from normal lungs, making it difficult to build a mechanical model . The proposed method used a few landmarks to capture the partialdeformation between the 3D surface mesh obtained from preoperative CT and the .intraoperative…

Solving the Multi-Agent Path Finding (MAPF) problem optimally is known to beNP-Hard for both make-span and total arrival time minimization . There is no dominatingoptimal MAPF algorithm that works well in all types of problems and no standard guidelines for when to use which algorithm .…

SemEval-2021 Task-4: Reading Comprehension of Abstract Meaning . Given a fill-in-the-blank-type question and a corresponding context, the task is to predict the most suitableword from a list of 5 options . We use encoders of transformers-based models pre-trained on themasked language modelling (MLM) task .…

Product embeddings have been heavily investigated in the past few years, serving as the cornerstone for a broad range of machine learning applications in e-commerce . Little is known on how and why they work from the theoretical standpoint, but little is known about them from a theoretical standpoint .…

Fine-tuning a pre-trained language model on much smaller datasets requires a carefully-designed pipeline to mitigate problems of the datasets such as lack of training data and imbalanced data . We propose a pipeline to adapt the general-purpose RoBERTa language model to aspecific text classification task: Vietnamese Hate Speech Detection .…

The MAP-Elites QD algorithm uses the learned latent space of the VAE as the search space for levels . The latent space captures the properties of the games whose levels we want to generate and blend, while MAP-elites searches this latent space to find a diverse set of levels optimizing a given objective such as playability .…

Non-pharmaceutical interventions (NPIs) are effective measures to contain apandemic. Yet, such control measures commonly have a negative effect on the economy . Here, we propose a macro-level approach to support resolving thisHealth-Economy Dilemma (HED) This study contributes to pandemicmodeling and simulation by providing a novel concept that elaborates onintegrating economic aspects while exploring the optimal moment to enable NPIs.…

In many multi-robot applications, mobile worker robots are often engaged in performing some tasks repetitively by following pre-computed trajectories . Asthese robots are battery-powered, they need to get recharged at regular intervals . We envision that in the future, a few mobile recharger robots will be employed to supply charge to the energy-deficient worker robots recurrently, to keep the overall efficiency of the system optimized .…

Explainable NLP (ExNLP) has increasingly focused on collecting human-annotated explanations . These explanations are used downstream in threeways: as data augmentation to improve performance on a predictive task, as aloss signal to train models to produce explanations for their predictions, and as a means to evaluate the quality of model-generated explanations .…

The stationary statistical properties of independent, identically distributed(i.i.d.) input symbols provide insights on the induced nonlinear interference(NLI) during fiber transmission . These statistical properties can be used inthe design of probabilistic amplitude shaping (PAS) The effective signal-to-noise ratio (SNR) in PAS has been shown to increase when the shaping blocklength decreases.…

Train companies are facing difficulties in gathering adequate images of defective equipment . Machine-learning models have developed a model using CycleGAN to generate artificial images instead of real images . These generated images play a vital role in enhancing the accuracy of the defect detection models, say researchers .…

We establish a phase transition known as the “all-or-nothing” phenomenon fornoiseless discrete channels . This class of models includes the Bernoulli grouptesting model and the planted Gaussian perceptron model . Previously, the existence of the phenomenon was only known in alimited range of parameters .…

Policymakers decide on alternative policies facing restricted budgets anduncertain, ever-changing future . Designing housing policies is difficult giving the heterogeneous characteristics of properties themselves and the intricacy of housing markets . We propose PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model .…

EmotionGIF2020 Challenge was held at the 8th International Workshop on Natural Language Processing for Social Media . The challenge required predictingaffective reactions to online texts . The novel dataset included 40Ktweets with their reaction GIFs . A total of 84 teams registered for the task .…