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AI advice is becoming increasingly popular, e.g., in investment and medical treatment decisions. As this advice is typically imperfect, decision-makers have to exert discretion as to whether actually follow that advice: they have to “appropriately” ...

A key goal of many computer science education efforts is to increase the number and diversity of students who persist in the field of computer science and into computing careers. Many interventions have been developed in computer science designed to ...

Virtual power plants (VPP) can increase reliability and efficiency of power systems with a high share of renewables. However, their adoption largely depends on their profitability, which is difficult to maximize due to the heterogeneity of their ...

Misinformation on social media has become a serious concern. Marking news stories with credibility indicators, possibly generated by an AI model, is one way to help people combat misinformation. In this paper, we report the results of two randomized ...

With the proliferation of high bandwidth cameras and AR/VR devices, and their increasing use in situation awareness applications, edge computing is gaining prominence to meet the throughput requirements of such applications. This work focuses on camera ...

Machine Learning models can output confident but incorrect predictions. To address this problem, ML researchers use various techniques to reliably estimate ML uncertainty, usually performed on controlled benchmarks once the model has been trained. We ...

Deep hashing based retrieval models have been widely used in large-scale image retrieval systems. Recently, there has been a surging interest in studying the adversarial attack problem in deep hashing based retrieval models. However, the effectiveness ...

Distributed solar energy resources (DSERs) in smart grid systems are rapidly increasing due to the steep decline in solar module prices. This DSER penetration has prompted utilities to balance the real-time supply and demand of electricity proactively. ...

Decision tree is the core algorithm of the random forest learning that has been widely applied to classification and regression problems in the machine learning field. For avoiding underfitting, a decision tree algorithm will stop growing its tree model ...

Wave energy is a fast-developing and promising renewable energy resource. The primary goal of this research is to maximise the total harnessed power of a large wave farm consisting of fully-submerged three-tether wave energy converters (WECs). Energy ...

Automated algorithm configuration procedures such as SMAC, GGA++ and irace can often find parameter configurations that substantially improve the performance of state-of-the-art algorithms for difficult problems - e.g., a three-fold speedup in the ...

Society has come to rely on algorithms like classifiers for important decision making, giving rise to the need for ethical guarantees such as fairness. Fairness is typically defined by asking that some statistic of a classifier be approximately equal ...

Inattentional blindness is the psychological phenomenon that causes one to miss things in plain sight. It is a consequence of the selective attention in perception that lets us remain focused on important parts of our world without distraction from ...

There is now significant historical data available on decision making in organizations, consisting of the decision problem, what decisions were made, and how desirable the outcomes were. Using this data, it is possible to learn a surrogate model, and ...

Teachers use observational cues in the classroom to identify attentiveness of students and guide the pace of their lecture. However, effectiveness of this technique decreases with increasing class size. This paper presented an approach for automating ...

We present a digital assistance approach for applied metrology on near-symmetrical objects. In manufacturing, systematically measuring products for quality assurance is often a manual task, where the primary challenge for the workers lies in accurately ...

The widespread use of machine learning algorithms and the high level of expertise required to utilize them have fuelled the demand for solutions that can be used by non-experts. One of the main challenges non-experts face in applying machine learning to ...

Reviews on online shopping websites affect the buying decisions of customers, meanwhile, attract lots of spammers aiming at misleading buyers. Xianyu, the largest second-hand goods app in China, suffering from spam reviews. The anti-spam system of ...

Self-disclosure to others has a proven benefit for one’s mental health. It is shown that disclosure to computers can be similarly beneficial for emotional and psychological well-being. In this paper, we analyzed verbal and nonverbal behavior associated ...

This paper proposes using face as a touch surface and employing hand-over-face (HOF) gestures as a novel input modality for interaction with smartphones, especially when touch input is limited. We contribute InterFace, a general system framework that ...