Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 82 for “"Multiclass"”.
-
Bayesian Multilevel-multiclass Graphical Model
Gaussian graphical model has been a popular tool to investigate conditional dependency between random variables by estimating sparse precision matrices. Two problems have been discussed. One is to learn multiple Gaussian graphical models at multilevel from unknown classes. Another one is to select …
-
Stability and performance of multiclass queueing networks
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1997.
-
A nonparametric multiclass partitioning method for classification
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982.
-
Robust fluid control of multiclass queueing networks
… of robust optimization to the optimal control of multiclass queueing networks. We develop models that take into account the uncertainty of interarrival and service time in multiclass queueing network problems without assuming a specific probability distribution, while remaining highly tractable …
-
Policy robustness : robust stability of multiclass queueing networks
… global—relative to control policies—stability of multiclass queueing networks. In these, as is known, it is generally insufficient that the nominal utilization at each server is below 100%. Certain policies, although work conserving, may destabilize a network that satisfies the nominal-load …
-
Multiclass Origin-Destination Estimation Using Multiple Data Types
… algorithm, and offer important insights into the multiclass O-D estimation process with different types of data available.
-
A sparse coding approach to multiclass pixel labelling
In this thesis, we introduce a method for multiclass pixel labelling to facilitate scene understanding and semantic segmentation. Specifically, we focus on enforcing label consistency in local image regions through sparse modelling of image data. Individual pixels in an image may be assigned a …
-
A sparse coding approach to multiclass pixel labelling
In this thesis, we introduce a method for multiclass pixel labelling to facilitate scene understanding and semantic segmentation. Specifically, we focus on enforcing label consistency in local image regions through sparse modelling of image data. Individual pixels in an image may be assigned a …
-
Transfer learning by borrowing examples for multiclass object detection
Despite the recent trend of increasingly large datasets for object detection, there still exist many classes with few training examples. To overcome this lack of training data for certain classes, we propose a novel way of augmenting the training data for each class by borrowing and transforming …
-
Scheduling of multiclass queueing networks : bounds on achievable performance
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.
-
Towards Multiclass Damage Detection and Localization using Limited Vibration Measurements
… and progressive damage, and identification of multiclass damage, creating constraints to make them free of user-intervention and implemented using the modern sensors. The main objective of this thesis is to develop algorithms capable of damage identification and localization using limited …
-
Control of multiclass queueing systems with abandonments and adversarial customers
… areas. We model the surveillance scenario as a multiclass queueing system with customer abandonments, wherein the operational problem translates into developing service policies for a server in order to minimise the expected damage an adversarial customer can inflict on the system. We consider …
-
Multiclass intermodal network model : the use of combined model on system evaluations
… a combined network equilibrium model (CNEM) for multiclass travelers. The combined model projects mode split and traffic assignment/route choice simultaneously. The impact of transfer is being considered in the modeling process. In the second part, the output of CNEM model is used to evaluate an …
-
Scheduling multiclass queueing networks and job shops using fluid and semidefinite relaxations
… we study the optimal control problem for multiclass queueing networks in steady-state. A key difficulty is that the fluid relaxation, being transient in nature, does not readily yield a lower bound for the steady-state problem. For this reason, we use a class of lower bounds, based on …
-
Generalised, multilingual, optical Braille recognition models
… on OBR performance, by training standard multiclass (well adopted methodology) and novel multilabel (proposed in this work) models on different scenarios with resampled training data. These models are evaluated on unseen test data, both in-distribution and out-of-distribution, as well as …
-
Elliptical cost-sensitive decision tree algorithm - ECSDT
Cost-sensitive multiclass classification problems, in which the task of assessing the impact of the costs associated with different misclassification errors, continues to be one of the major challenging areas for data mining and machine learning. The literature reviews in this area show that most …
-
Development of a Bagging-based Ensemble Model for ECG Classification
… binary classification on the PTB dataset and multiclass classification on the MITBIH datasets. The findings indicate that the CNN model outperforms the other two models under the selected parameters and across ten epochs achieving 0.95 for binary classification and 0.96 for multiclass …
-
A regularization framework for active learning from imbalanced data
We consider the problem of building a viable multiclass classification system that minimizes training data, is robust to noisy, imbalanced samples, and outputs confidence scores along with its predications. These goals address critical steps along the entire classification pipeline that pertain to …
-
Automatic Classification and Segmentation of Patterned Martian Ground Using Deep Learning Techniques
… to identify images containing polygons, multiclass classification distinguishing different polygon types and semantic segmentation of polygon regions. Due to time and resource constraints, transfer learning is employed on state-of-the-art deep learning networks. Convolutional neural …
-
Probabilistic multiple kernel learning
… probabilistic data integration algorithms for multiclass decisions where an observation of interest is assigned to one of many categories based on a plurality of information channels.
Page 1 of 5