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Federal
Classification 16 recent views
National Aeronautics and Space Administration —
A supervised learning task involves constructing a mapping from an input data space (normally described by several features) to an output space. A set of training... -
Federal
MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING
National Aeronautics and Space Administration —
MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING MOHAMMAD SALIM AHMED, LATIFUR KHAN, NIKUNJ OZA, AND MANDAVA RAJESWARI Abstract.... -
Federal
Classification of Mars Terrain Using Multiple Data Sources
National Aeronautics and Space Administration —
Classification of Mars Terrain Using Multiple Data Sources Alan Kraut1, David Wettergreen1 ABSTRACT. Images of Mars are being collected faster than they can be... -
Federal
ADAPTIVE FAULT DETECTION ON LIQUID PROPULSION SYSTEMS WITH VIRTUAL SENSORS: ALGORITHMS AND ARCHITECTURES
National Aeronautics and Space Administration —
Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an... -
Federal
Distributed Anomaly Detection using 1-class SVM for Vertically Partitioned Data
National Aeronautics and Space Administration —
There has been a tremendous increase in the volume of sensor data collected over the last decade for different monitoring tasks. For example, petabytes of earth... -
Federal
nu-Anomica algorithm
National Aeronautics and Space Administration —
One-class nu-Support Vector machine (SVMs) learning technique maps the input data into a much higher dimensional space and then uses a small portion of the training... -
Federal
A Modeling Framework for Prognostic Decision Making and its Application to UAV Mission Planning
National Aeronautics and Space Administration —
The goal of prognostic decision making (PDM) is to utilize information on anticipated system health changes in selecting future actions. One of the key challenges in... -
Federal
Sparse Solutions for Single Class SVMs: A Bi-Criterion Approach
National Aeronautics and Space Administration —
In this paper we propose an innovative learning algorithm - a variation of One-class Support Vector Machines (SVMs) learning algorithm to produce sparser solutions... -
Federal
Unsupervised Anomaly Detection for Liquid-Fueled Rocket Prop...
National Aeronautics and Space Administration —
Title: Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring. Abstract: This article describes the results of applying four... -
Federal
Optimal Alarm Systems
National Aeronautics and Space Administration —
An optimal alarm system is simply an optimal level-crossing predictor that can be designed to elicit the fewest false alarms for a fixed detection probability. It... -
Federal
KEYWORD SEARCH IN TEXT CUBE: FINDING TOP-K RELEVANT CELLS
National Aeronautics and Space Administration —
KEYWORD SEARCH IN TEXT CUBE: FINDING TOP-K RELEVANT CELLS BOLIN DING, YINTAO YU, BO ZHAO, CINDY XIDE LIN, JIAWEI HAN, AND CHENGXIANG ZHAI Abstract. We study the... -
Federal
Pseudo-Label Generation for Multi-Label Text Classification
National Aeronautics and Space Administration —
With the advent and expansion of social networking, the amount of generated text data has seen a sharp increase. In order to handle such a huge volume of text data,... -
Federal
Communication Optimizations for a Wireless Distributed Prognostic Framework
National Aeronautics and Space Administration —
Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication... -
Federal
Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation
National Aeronautics and Space Administration —
Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper... -
Federal
nu-Anomica: A Fast Support Vector Based Anomaly Detection Technique
National Aeronautics and Space Administration —
In this paper we propose $\nu$-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the... -
Federal
Deterministic Compilation of Temporal Safety Properties in Explicit State Model Checking
National Aeronautics and Space Administration —
The translation of temporal logic specifications constitutes an essen- tial step in model checking and a major influence on the efficiency of formal verification via... -
Federal
ν-Anomica: A Fast Support Vector based Novelty Detection Technique
National Aeronautics and Space Administration —
In this paper we propose ν-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the benchmark... -
Federal
Key Real-World Applications of Classifier Ensembles
National Aeronautics and Space Administration —
Broad classes of statistical classification algorithms have beendeveloped and applied successfully to a wide range of real worlddomains. In general, ensuring that the... -
Federal
Novel Methods for Predicting Photometric Redshifts
National Aeronautics and Space Administration —
We calculate photometric redshifts from the Sloan Digital Sky Survey Main Galaxy Sample, The Galaxy Evolution Explorer All Sky Survey, and The Two Micron All Sky... -
Federal
SPATIALLY ADAPTIVE SEMI-SUPERVISED LEARNING WITH GAUSSIAN PROCESSES FOR HYPERSPECTRAL DATA ANALYSIS
National Aeronautics and Space Administration —
SPATIALLY ADAPTIVE SEMI-SUPERVISED LEARNING WITH GAUSSIAN PROCESSES FOR HYPERSPECTRAL DATA ANALYSIS GOO JUN * AND JOYDEEP GHOSH* Abstract. A semi-supervised learning...