Yara Rizk

Yara Rizk
American University of Beirut | AUB · Department of Electrical and Computer Engineering

About

26
Publications
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498
Citations

Publications

Publications (26)
Article
Full-text available
Recurrent neural networks (RNN) have been successfully applied to various sequential decision-making tasks, natural language processing applications, and time-series predictions. Such networks are usually trained through back-propagation through time (BPTT) which is prohibitively expensive, especially when the length of the time dependencies and th...
Article
Full-text available
Bright spots, strong indicators of the existence of hydrocarbon accumulations, have been primarily used by geophysicists in oil and gas exploration. Recently, machine-learning algorithms, adopted to automate bright spot detection, have mainly relied on feature extraction and shallow classification workflows to achieve an 85.4% F1 score at best, on...
Preprint
Full-text available
Recurrent neural networks (RNN) have been successfully applied to various sequential decision-making tasks, natural language processing applications, and time-series predictions. Such networks are usually trained through back-propagation through time (BPTT) which is prohibitively expensive, especially when the length of the time dependencies and th...
Article
Full-text available
The enormous number of articles published daily on the internet, by a diverse array of authors, often offers misleading or unwanted information, rendering activities such as sports betting riskier. As a result, extracting meaningful and reliable information from these sources becomes a time consuming and near impossible task. In this context, label...
Preprint
Full-text available
Bright spots have been the primary approach to identify hydrocarbon bearing formations. Specifically, 3D seismic texture analysis has been employed to identify such locations of interest. However, raw seismic data is large in volume and requires a plethora of prepro-cessing techniques before meaningful information can be extracted. Hence, bright sp...
Conference Paper
Medical students undergo exams, called “Objective Structured Clinical Examinations” (OSCEs), to assess their medical competence in clinical tasks. In these OSCEs, a medical student interacts with a standardized patient, asking questions to complete a clinical assessment of the patient’s medical case. In real OSCEs, standardized patients or “Actors”...
Article
The emergence of the Internet of things and the widespread deployment of diverse computing systems have led to the formation of heterogeneous multi-agent systems (MAS) to complete a variety of tasks. Motivated to highlight the state of the art on existing MAS while identifying their limitations, remaining challenges, and possible future directions,...
Conference Paper
When natural disasters strike, annotated images and texts flood the Internet, and rescue teams become overwhelmed to prioritize often scarce resources, while relying heavily on human input. In this paper, a novel multi-modal approach is proposed to automate crisis data analysis using machine learning. Our multi-modal two-stage framework relies on c...
Preprint
Full-text available
The emergence of the Internet of things and the wide spread deployment of diverse computing systems have led to the formation of heterogeneous multi-agent systems (MAS) to complete a variety of tasks. Motivated to highlight the state of the art on existing MAS while identifying their limitations, remaining challenges and possible future directions,...
Preprint
Full-text available
When natural disasters strike, annotated images and texts flood the Internet, and rescue teams become overwhelmed to prioritize often scarce resources, while relying heavily on human input. In this paper, a novel multi-modal approach is proposed to automate crisis data analysis using machine learning. Our multi-modal two-stage framework relies on c...
Article
Full-text available
With the “last mile” of the delivery process being the most expensive phase, autonomous package delivery systems are gaining traction as they aim for faster and cheaper delivery of goods to city, urban and rural destinations. This interest is further fueled by the emergence of e-commerce, where many applications can benefit from autonomous package...
Article
Full-text available
In this work, we established the foundations of a framework with the goal to build an end-to-end naturalistic expressive listening agent. The project was split into modules for recognition of the user’s paralinguistic and nonverbal expressions, prediction of the agent’s reactions, synthesis of the agent’s expressions and data recordings of nonverba...
Article
Recurrent neural networks (RNN) are a type of artificial neural networks (ANN) that have been successfully applied to many problems in artificial intelligence. However, they are expensive to train since the number of learned weights grows exponentially with the number of hidden neurons. Non-iterative training algorithms have been proposed to reduce...
Article
Full-text available
Intelligent transport systems, efficient electric grids, and sensor networks for data collection and analysis are some examples of the multi-agent systems (MAS) that cooperate to achieve common goals. Decision making is an integral part of intelligent agents and MAS that will allow such systems to accomplish increasingly complex tasks. In this surv...
Conference Paper
Full-text available
Social media has recently become a digital lifeline used to relay information and locate survivors in disaster situations. Currently, officials and volunteers scour social media for any valuable information; however, this approach is implausible as millions of posts are shared by the minute. Our goal is to automate actionable information extraction...
Article
Full-text available
The failure of shallow neural network architectures in replicating human intelligence led the machine learning community to focus on deep learning, to computationally match human intelligence. The wide availability of increasing computing power coupled with the development of more efficient training algorithms have allowed the implementation of dee...
Article
Bright spots have been the primary approach to identify hydrocarbon bearing formations. Specifically, three-dimensional (3-D) seismic texture analysis has been employed to identify such locations of interest. However, raw seismic data are large in volume and require a plethora of preprocessing techniques before meaningful information can be extract...
Conference Paper
Full-text available
The emergence of the big data problem has pushed the machine learning research community to develop unsupervised, distributed and computationally efficient learning algorithms to benefit from this data. Extreme learning machines (ELM) have gained popularity as a neuron based architecture with fast training time and good generalization. In this work...
Conference Paper
Full-text available
In the big data era, the need for fast robust machine learning techniques is rapidly increasing. Deep network architectures such as cortical algorithms are challenged by big data problems which result in lengthy and complex training. In this paper, we present a distributed cortical algorithm implementation for the unsupervised learning of big data...
Conference Paper
Full-text available
We propose in this paper, Face2Mus, a mobile application that streams music from online radio stations after identifying the user's emotions, without interfering with the device’s usage. Face2Mus streams songs from online radio stations and classifies them into emotion classes based on audio features using an energy aware support vector machin...
Conference Paper
Despite support vector machines' (SVM) robustness and optimality, SVM do not scale well computationally. Suffering from slow training convergence on large datasets, SVM online testing time can be suboptimal because SVM write the classifier hyper-plane model as a sum of support vectors that could total as much as half the datasets. Motivated to spee...
Conference Paper
Full-text available
The abundance of information on the World Wide Web and the existing content authentication mechanisms render the ability to efficiently find factual information often challenging and time consuming. This situation calls to the user’s judgment and knowledge about the sought topic. For sports articles, more specifically, where information is often us...

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Projects

Project (1)
Project
Different machine learning algorithms on social and cultural data