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Deep neural networks (DNNs) are increasingly used in real-world applications (e.g. facial recognition). This has resulted in concerns about the fairness of decisions made by these models. Various notions and measures of fairness have been proposed to ...

Recent advances in neural networks (NNs) and their applications in deep learning techniques have made the security aspects of NNs an important and timely topic for fundamental research. In this paper, we survey the security challenges and opportunities ...

Evading oppressive internet censorship is possible, but discovering how is difficult and time-consuming for humans. Geneva is a genetic algorithm that automatically discovers and implements censorship circumvention strategies---many of which were long ...

Modern 3D printers are capable of printing large-size light-field displays at high-resolutions. However, optimizing such displays in full 3D volume for a given light-field imagery is still a challenging task. Existing light field displays optimize over ...

The COVID-19 pandemic has posed grand challenges to policy makers, raising major social conflicts between public health and economic resilience. Policies such as closure or reopen of businesses are made based on scientific projections of infection risks ...

Traditionally, historical crimes and socioeconomic data have been used to understand crime in cities and to build crime prediction models. Nevertheless, the increasing availability of mobility data from cell phones to location-based services, has ...

Alcoholism, also known as Alcohol Use Disorder (AUD), is a serious problem affecting millions of people worldwide. Recovery from AUD is known to be challenging and often leads to relapse at various points after enrolling in a rehabilitation program such ...

This article attempts to bridge the gap between widely discussed ethical principles of Human-centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are developed and implemented in multiple organizational structures, I ...

Variational Quantum Circuits (VQCs), or the so-called quantum neural-networks, are predicted to be one of the most important near-term quantum applications, not only because of their similar promises as classical neural-networks, but also because of ...

Detecting anomalous activity in human mobility data has a number of applications, including road hazard sensing, telematics-based insurance, and fraud detection in taxi services and ride sharing. In this article, we address two challenges that arise in ...

Algorithms and machine learning models, including the decisions made by these models, are becoming ubiquitous in our daily life, including hiring. We make no value judgment regarding this development; rather, we simply acknowledge that it is quickly ...

Model-based reinforcement learning algorithms make decisions by building and utilizing a model of the environment. However, none of the existing algorithms attempts to infer the dynamics of any state-action pair from known state-action pairs before ...

Speech input is a primary method of interaction for blind mobile device users, yet the process of dictating and reviewing recognized text through audio only (i.e., without access to visual feedback) has received little attention. A recent study found ...

External ventricular drainage (EVD) is a high-risk medical procedure that involves inserting a catheter inside a patient’s skull, through the brain and into a ventricle, to drain cerebrospinal fluid and thus relieve elevated intracranial pressure. Once ...

Human activity recognition (HAR) from wearable sensor data has recently gained widespread adoption in a number of fields. However, recognizing complex human activities, postural and rhythmic body movements (e.g. dance, sports) is challenging due to the ...

Researchers and censoring regimes have long engaged in a cat-and-mouse game, leading to increasingly sophisticated Internet-scale censorship techniques and methods to evade them. In this paper, we take a drastic departure from the previously manual ...

Air Navigation Service Providers (ANSP) worldwide have been making a considerable effort for the development of a better method to monitor conformance to the planned routes and detect anomalies within a particular airspace. Conformance monitoring and ...

Cycling provides various benefits to cyclists and cities. Nevertheless, the growth of cycling is still hindered by the lack of citywide information about perceived cycling safety. Providing cyclists with information about the safest routes could help ...

Auto-encoder is an important architecture to understand point clouds in an encoding and decoding procedure of self reconstruction. Current auto-encoder mainly focuses on the learning of global structure by global shape reconstruction, while ignoring the ...