Browsing Department of Computer Science and Engineering by Title
Now showing items 346-365 of 606
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JSSpe: A Symbolic Partial Evaluator for JavaScript
(2018-04-19)Currently, JavaScript is one of the mostly used programming languages for Web and Mobile platforms. This brings a large demand for optimization and smarter resource allocation of the applications written in JavaScript. ... -
KOPOS: A FRAMEWORK TO STUDY AND DETECT PHYSICAL AND COGNITIVE FATIGUE CONCURRENTLY
(2021-05-12)Fatigue is one of the most prevalent phenomena in human beings, and yet its detection is highly subjective and poorly understood. The phenomenon of fatigue has a huge impact on performance, the ability to execute tasks ... -
Language Pre-Training and Auxiliary Tasks for Vision and Language Navigation
(2022-01-06)The Vision and Language Navigation task came to life from the idea that we can build a robot or an autonomous system that can be instructed in human language and that will navigate using the instructions given. For example, ... -
LARGE-SCALE DEEP LEARNING WITH APPLICATION IN MEDICAL IMAGING AND BIO-INFORMATICS
(2018-11-27)With the recent advancement of the deep learning technology in the artificial intelligence area, nowadays people's lives have been drastically changed. However, the success of deep learning technology mostly relies on ... -
Learning Abstractions for Planning
(2020-06-03)Planners for hard problems must exploit domain-specific structure to find solutions efficiently. Yet, hand-engineered solutions and optimizations are often expensive and difficult or impossible to adapt to other problems. ... -
LEARNING CAUSAL BOUNDS USING MARGINAL INDEPENDENCE INFORMATION WITH APPLICATIONS TO GENE EXPRESSION ANALYSIS
(2022-03-14)Discovering causal relations is a fundamental goal of science. Randomized controlled experiments were often considered to be the only reliable method for tackling this task. However, in recent years, various causal discovery ... -
LEARNING EMBEDDINGS FOR WEARABLE-BASED HUMAN ACTIVITY ANALYSIS
(2020-09-04)The embedded sensors in widely used smartphones, wearable devices and smart environments make the sensor data stream of human activity more accessible. With the development of deep neural networks, extensive studies have ... -
Learning Equivalent Input Channel Mappings And Generalized Features For Pattern Transfer
(Computer Science & Engineering, 2013-10-22)In many real-world modeling applications, it is needed to detect the origin of the patterns of the input data in addition to find the patterns themselves. Having the input data generated by a systematically organized set ... -
LEARNING FOR CLINICAL OUTCOME PREDICTION FROM BIG MEDICAL DATA
(2019-08-09)With the advance of recent technological innovations, nowadays scientists can easily capture and store tremendous amounts of different types of medical data such as Computed Tomography (CT), Magnetic Resonance Imaging ... -
LEARNING FROM WIZARD-OF-OZ USING DYNAMIC USER MODELING
(2017-05-15)Socially assistive robotics (SAR) is a field of study that combines assistive robotics with socially interactive robotics where the goal of the robot is to provide assistance to human users through social interaction. The ... -
Learning Health Information From Floor Sensor Data Within A Pervasive Smart Home Environment
(2020-09-02)Spatial and temporal gait analysis can provide useful measures for determining a person’s state of health while also identifying deviations in day-to-day activity. The SmartCare project is a multi-discipline health ... -
LEARNING HIERARCHICAL TRAVERSABILITY REPRESENTATION FOR EFFICIENT MULTI-RESOLUTION PATH PLANNING
(2021-05-13)Path finding on grid-based obstacle maps is an important and much studied problem with applications in robotics and autonomy. Traditionally, in the AI community, heuristic search methods (e.g. based on Dijkstra and A*, or ... -
Learning Partially Observable Markov Decision Processes Using Abstract Actions
(Computer Science & Engineering, 2014-03-10)Transfer learning and Abstraction are among the new and most interesting research topics in AI and address the use of learned knowledge to improve learning performance in subsequent tasks. While there has been significant ... -
LEARNING PERCEPTION TO ACTION MAPPING FOR FUNCTIONAL IMITATION
(2016-12-09)Imitation leaning is the learning of advanced behavior whereby an agent acquires a skill by observing another's behavior while performing the same skill. The main objective of imitation learning is to make robots usable ... -
Learning Representations Using Reinforcement Learning
(2019-05-09)The framework of reinforcement learning is a powerful suite of algorithms that can learn generalized solutions to complex decision making problems. However, the applications of reinforcement learning algorithms to traditional ... -
LEARNING ROBOT MANIPULATION TASKS VIA OBSERVATION
(2019-12-06)The coexistence of humans and robots has been the aspiration of many scientific endeavors in the past century. Most anthropomorphic or industrial robots are highly articulated and complex machines, which are designed to ... -
Learning State And Action Space Hierarchies For Reinforcement Learning Using Action-Dependent Partitioning
(Computer Science & Engineering, 2007-08-23)Autonomous systems are often dicult to program. Reinforcement learning (RL) is an attractive alternative, as it allows the agent to learn behavior on the basis of sparse, delayed reward signals provided only when the ... -
LEARNING TO GENERATE INDIVIDUAL DATA SEQUENCE FROM POPULATION STATISTICS USING DYNAMIC BAYESIAN NETWORKS
(2018-05-11)Data collection rose exponentially with the dawn of the 21st Century, However the most important data to humans, individual health data, is difficult to get approved for public research, as medical history is very sensitive ... -
LEARNING TOPOLOGY PRESERVING EMBEDDINGS FOR SPEEDING UP NEAREST NEIGHBOR RETRIEVAL
(2022-05-06)Given a database of objects and a query object, it’s possible to gather a number of the closest neighbors to the query object. This operation is important to a number of diverse fields such as computer vision, content- based ... -
LEARNING TRANSFERABLE META-POLICIES FOR HIERARCHICAL TASK DECOMPOSITION AND PLANNING COMPOSITION
(2019-12-16)In real world scenarios where situated agents are faced with dynamic, high-dimensional, partially observable environments with action and reward uncertainty, the traditional states space Reinforcement Learning (RL) becomes ...