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Dynamic node clustering in hierarchical optical data center network architectures
(Massachusetts Institute of Technology, 2020)
During the past decade an increasing trend in the Data Center Network's traffic has been observed. This traffic is characterized mostly by many small bursty flows (mice) that last for less than few milliseconds as well as ...
Anomaly detection methods for detecting cyber attacks in industrial control systems
(Massachusetts Institute of Technology, 2020)
Industrial control systems (ICS) are pervasive in modern society and increasingly under threat of cyber attack. Due to the critical nature of these systems, which govern everything from power and wastewater plants to ...
School choice : a discrete optimization approach
(Massachusetts Institute of Technology, 2020)
An equitable and flexible mechanism for assigning students to schools is a major concern for many school districts. The school a student attends dramatically impacts the quality of education, access to resources, family ...
Information fusion for an unmanned underwater vehicle through probabilistic prediction and optimal matching
(Massachusetts Institute of Technology, 2020)
This thesis presents a method for information fusion for an unmanned underwater vehicle (UUV).We consider a system that fuses contact reports from automated information system (AIS) data and active and passive sonar sensors. ...
Inventory positioning in modern retail
(Massachusetts Institute of Technology, 2021)
Modern retail has been significantly affected by the surge in online platforms and product options. Customers have comfortably settled into an omni-channel model, in which they buy different products through different ...
Leveraging machine learning to solve The vehicle Routing Problem with Time Windows
(Massachusetts Institute of Technology, 2020)
The Vehicle Routing Problem with Time Windows (VRPTW) has been widely studied in the Operations Research (OR) literature given its increasingly widespread applications, ranging from school bus scheduling to packages delivery. ...
Understanding neural network sample complexity and interpretable convergence-guaranteed deep learning with polynomial regression
(Massachusetts Institute of Technology, 2020)
We first study the sample complexity of one-layer neural networks, namely the number of examples that are needed in the training set for such models to be able to learn meaningful information out-of-sample. We empirically ...
Prescriptive methods for adaptive learning
(Massachusetts Institute of Technology, 2020)
It is undeniable that recent world events and globalization have transformed online learning into one of the main channels for education. Online learning has become a necessity, not a luxury. Universities, schools, and ...
Ship-pack replenishment optimization in a two-echelon distribution system with lost sales and seasonal product obsolescence
(Massachusetts Institute of Technology, 2021-06)
As a retailer attempts to leverage a two-echelon distribution system to forward-deploy inventory, a number of cost elements must be considered when deciding the quantity of a given SKU to replenish to the forward-deployed ...
Improving prior knowledge assessment in process characterization
(Massachusetts Institute of Technology, 2020)
A critical aspect of biologics manufacturing is creating a safe, reliable and consistent manufacturing process. The manufacturing process design includes process characterization (PC) experiments to demonstrate process ...