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Hardware security is currently a very influential domain, where each year countless works are published concerning attacks against hardware and countermeasures. A significant number of them use machine learning, which is proven to be very effective in ...

Machine learning models are becoming pervasive in high-stakes applications. Despite their clear benefits in terms of performance, the models could show discrimination against minority groups and result in fairness issues in a decision-making process, ...

In the big data era, the relationship between entities becomes more complex. Therefore, graph (or network) data attracts increasing research attention for carrying complex relational information. For a myriad of graph mining/learning tasks, graph neural ...

Conversational agents, or commonly known as dialogue systems, have gained escalating popularity in recent years. Their widespread applications support conversational interactions with users and accomplishing various tasks as personal assistants. However,...

With the availability of massive labeled training data, powerful machine learning models can be trained. However, the traditional I.I.D. assumption that the training and testing data should follow the same distribution is often violated in reality. ...

Social media sites such as Twitter and Facebook have connected billions of people and given the opportunity to the users to share their ideas and opinions instantly. That being said, there are several negative consequences as well such as online ...

Knowledge in NLP has been a rising trend especially after the advent of large-scale pre-trained models. Knowledge is critical to equip statistics-based models with common sense, logic and other external information. In this tutorial, we will introduce ...

Robot navigation in crowded public spaces is a complex task that requires addressing a variety of engineering and human factors challenges. These challenges have motivated a great amount of research resulting in important developments for the fields of ...

Robotic vision, otherwise known as computer vision for robots, is a critical process for robots to collect and interpret detailed information related to human actions, goals, and preferences, enabling robots to provide more useful services to people. This ...

Given the popular presupposition of human reasoning as the standard for learning and decision-making, there have been significant efforts and a growing trend in research to replicate these innate human abilities in artificial systems. As such, topics ...

In Over the last few years, Machine Learning (ML), and particularly Deep Learning (DL), has made great strides and has been successfully deployed in many real-world applications such as healthcare, customer care, finance, autonomous driving etc. One of ...

In the relatively short history of machine learning, the subtle balance between engineering and theoretical progress has been proved critical at various stages. The most recent wave of AI has brought to the IR community powerful techniques, particularly ...

Stance detection (also known as stance classification, stance prediction, and stance analysis) is a problem related to social media analysis, natural language processing, and information retrieval, which aims to determine the position of a person from a ...

Graphs are widely used for abstracting complex systems of interacting objects, such as social networks, knowledge graphs, and traffic networks, as well as for modeling molecules, manifolds, and source code. To model such graph-structured data, graph ...

The saying Garbage In, Garbage Out resonates perfectly within the machine learning and artificial intelligence community. While there has been considerable ongoing effort for improving the quality of models, there is relatively less focus on ...

Usually data scientists are adept in deriving valuable insights from data by applying appropriate machine learning algorithms. However, data scientists are usually not skilled in developing or operating production level software which is the domain of ...

This tutorial will elaborate on various available resources for the natural language generation (NLG) tasks in code-mixed languages. We will also discuss the adaptability, limitations, and challenges with various evaluation metrics for the code-mixed ...

Recent years have seen an unprecedented spread of Unmanned Aerial Vehicles (UAVs, or “drones”), which are highly useful for both civilian and military applications. Flight safety is a crucial issue in UAV navigation, having to ensure accurate compliance ...

Recently, Machine Learning (ML, for short) has been successfully applied to database indexing. Initial experimentation on Learned Indexes has demonstrated better search performance and lower space requirements than their traditional database ...

The main focus of object detection, one of the most challenging problems in computer vision (CV), is to predict a set of bounding boxes and category labels for each object of interest in an image or in a point cloud. As such, object detection has a ...