Index Catalog // ScholarsArchive@OSU

Calibrating recurrent sliding window classifiers for sequential supervised learning

Creator:: Joshi, Saket, Dietterich, Thomas G., and Oregon State University. School of Electrical Engineering and Computer Science
Abstract:: Sequential supervised learning problems involve assigning a class label to each item in a sequence. Examples include part of speech tagging and text to speech mapping. A very general-purpose strategy for solving such problems is to construct a recurrent sliding window (RSW) classifier which maps some window of the input...
Resource Type:: Technical Report
Full Text:: � ough��f � �In��f�� Another example is the problem of part�of�speech tagging M�arquez� Padr�o

Exploring Outlier Exposure Methods for Deep Margin-Based Anomaly Detection

Creator:: Noel, Thomas
Abstract:: In standard training regimes, one assumes that the classes presented to a model constitute all of the classes that the model will encounter when it is deployed. In real deployment scenarios, however, a model can sometimes encounter situations or objects that it has never seen. When these scenarios are safety-critical,...
Resource Type:: Capstone Project
Full Text:: Representations, 2019. [5] Yen-Chang Hsu, Yilin Shen, Hongxia Jin, and Zsolt Kira. Generalized odin: De- tecting

Calibrating recurrent sliding window classifiers for sequential supervised learning

Creator:: Joshi, Saket Subhash
Abstract:: Sequential supervised learning problems involve assigning a class label to each item in a sequence. Examples include part-of-speech tagging and text-to-speech mapping. A very general-purpose strategy for solving such problems is to construct a recurrent sliding window (RSW) classifier, which maps some window of the input sequence plus some number...
Resource Type:: Masters Thesis

The sum of its parts : investigating the component pieces of GenderMag

Creator:: Hill, Charles
Abstract:: Previous work introduced the GenderMag method, a software inspection method used to help software creators identify features within their software that are not gender-inclusive. Inclusiveness of software (gender or otherwise) matters because supporting diversity matters—it is well-known that the more diverse a group of problem-solvers, the higher the quality of...
Resource Type:: Masters Thesis
Full Text:: M. Burnett Previous work introduced the GenderMag method, a software inspection method used

Newcomers’ Barriers. . . Is That All? An Analysis of Mentors’ and Newcomers’ Barriers in OSS Projects

Creator:: Balali, Sogol
Abstract:: Newcomers’ seamless onboarding is important for open collaboration communi- ties, particularly those that leverage outsiders’ contributions to remain sustainable. Nevertheless, previous work shows that OSS newcomers often face several barriers to contribute, which lead them to lose motivation and even give up on contributing. A well-known way to help newcomers...
Resource Type:: Masters Thesis
Full Text:: Assigned or ID Gender Mentoring OSS Industry choose to P1 M 8 5 11 Chose to P2 M 2 3 – Both P3 M 3 3

Semantic embodied navigation : developing agents that navigate from language and vision

Creator:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation

Structured learning with latent variables : theory and algorithms

Creator:: Zhao, Kai
Abstract:: Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
Resource Type:: Dissertation
Full Text:: length of the meaning representations. |θ|M is the number of parameters without the word embeddings

Knowledge Base Completion Leveraging Natural Language Data

Creator:: Shahbazi, Hamed
Abstract:: Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
Resource Type:: Dissertation
Full Text:: 2.2 Global accuracy minus local accuracy per bin of rarity measure Pr(e|m) which is scaled to (0, 100

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

Creator:: Aziere, Nicolas
Abstract:: This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Resource Type:: Dissertation

ScholarsArchive@OSU

Calibrating recurrent sliding window classifiers for sequential supervised learning

Exploring Outlier Exposure Methods for Deep Margin-Based Anomaly Detection

Calibrating recurrent sliding window classifiers for sequential supervised learning

The sum of its parts : investigating the component pieces of GenderMag

Newcomers’ Barriers. . . Is That All? An Analysis of Mentors’ and Newcomers’ Barriers in OSS Projects

Semantic embodied navigation : developing agents that navigate from language and vision

Structured learning with latent variables : theory and algorithms

Knowledge Base Completion Leveraging Natural Language Data

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

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