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Digital data archives play essential roles in knowledge infrastructures bymediating access to data within and between communities. This three-yearqualitative study of DANS, a digital data archive containing more than 50 yearsof heterogeneous data types, provides new insights to the uses, users...

Driver gaze has been shown to be an excellent surrogate for driver attentionin intelligent vehicles. With the recent surge of highly autonomous vehicles,driver gaze can be useful for determining the handoff time to a human driver.While there has been significant improvement in personalized driver...

Single image super-resolution (SR) via deep learning has recently gainedsignificant attention in the literature. Convolutional neural networks (CNNs)are typically learned to represent the mapping between low-resolution (LR) andhigh-resolution (HR) images/patches with the help of training examples...

We apply linear network coding (LNC) to broadcast a block of data packetsfrom one sender to a set of receivers via lossy wireless channels, assumingeach receiver already possesses a subset of these packets and wants the rest.We aim to characterize the average packet decoding delay (APDD), which...

This paper presents a new algorithm for the lossy compression of scalar datadefined on 2D or 3D regular grids, with topological control. Certain techniquesallow users to control the pointwise error induced by the compression. However,in many scenarios it is desirable to control in a similar way the...

The automated theorem prover Leo-III for classical higher-order logic withHenkin semantics and choice is presented. Leo-III is based on extensionalhigher-order paramodulation and accepts every common TPTP dialect (FOF, TFF,THF), including their recent extensions to rank-1 polymorphism (TF1, TH1)...

Deep convolutional neural networks (CNNs) have shown appealing performance onvarious computer vision tasks in recent years. This motivates people to deployCNNs to realworld applications. However, most of state-of-art CNNs requirelarge memory and computational resources, which hinders the deployment...

Device to device (D2D) communication underlaying LTE can be used todistribute traffic loads of eNBs. However, a conventional D2D link iscontrolled by an eNB, and it still remains burdens to the eNB. We propose acompletely distributed power allocation method for D2D communicationunderlaying LTE using...

Motivated by the popularity of online ride and delivery services, we studynatural variants of classical multi-vehicle minimum latency problems where theobjective is to route a set of vehicles located at depots to serve requestlocated on a metric space so as to minimize the total latency. In this...

People use rich prior knowledge about the world in order to efficiently learnnew concepts. These priors - also known as "inductive biases" - pertain to thespace of internal models considered by a learner, and they help the learnermake inferences that go beyond the observed data. A recent study found...

In many shopping scenarios, e.g., in online shopping, customers have a largemenu of options to choose from. However, most of the buyers do not browse allthe options and make decision after considering only a small part of the menu.To study such buyer's behavior we consider the standard Bayesian...

In this paper, we present some applications of a difference equation ofdegree k in Cryptography and Coding Theory.

Many-core accelerators, as represented by the XeonPhi coprocessors andGPGPUs, allow software to exploit spatial and temporal sharing of computingresources to improve the overall system performance. To unlock this performancepotential requires software to effectively partition the hardware resource...

Imitation learning holds the promise to address challenging robotic taskssuch as autonomous navigation. It however requires a human supervisor tooversee the training process and send correct control commands to robotswithout feedback, which is always prone to error and expensive. To minimizehuman...

This paper presents a real-time programming and parameter reconfigurationmethod for autonomous underwater robots in human-robot collaborative tasks.Using a set of intuitive and meaningful hand gestures, we develop asyntactically simple framework that is computationally more efficient than acomplex...

The provision of reliable and efficient communication is a key requirementfor the deployment of autonomous cars as well as for future IntelligentTransportation Systems (ITSs) in smart cities. Novel communicationstechnologies will have to face highly-complex and extremely dynamic networktopologies in...

Dependency treebank is an important resource in any language. In this paper,we present our work on building BKTreebank, a dependency treebank forVietnamese. Important points on designing POS tagset, dependency relations, andannotation guidelines are discussed. We describe experiments on POS tagging...

Generative adversarial networks (GANs) are a family of generative models thatdo not minimize a single training criterion. Unlike other generative models,the data distribution is learned via a game between a generator (the generativemodel) and a discriminator (a teacher providing training signal)...

We consider the problem of approximate reduction of non-deterministicautomata that appear in hardware-accelerated network intrusion detectionsystems (NIDSes). We define an error distance of a reduced automaton from theoriginal one as the probability of packets being incorrectly classified by...