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.
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Showing 1 to 20 of 38 for “"Weak Supervision"”.
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Information extraction with weak supervision
… explores the development and application of weak supervision techniques to address key challenges in three fundamental information extraction (IE) tasks: Named Entity Recognition (NER), Relation Extraction (RE), and Entity Linking (EL). Traditional supervised learning methods in these domains …
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Learning Object Detection with Weak Supervision
… for reducing costs is to train models with weak supervision, which provides a good trade-off between model performance and annotation efficiency. This thesis dedicates to weakly supervised learning in two object-centered application scenarios, i.e., general object detection and RGB-D salient …
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Learning with Constraint-Based Weak Supervision
… several alternatives to supervised learning. Weak supervision is one such alternative. Weak supervision or weakly supervised learning involves using noisy labels (weak signals of the data) from multiple sources to train machine learning systems. A weak supervision model aggregates multiple …
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Learning from Structured Data with Weak Supervision
… characteristics is learning the AI/ML model with weak forms of supervision. To fulfil such goals, we develop a variety of learning methods on a range of structured data representations. We start by working on point clouds; we developed a universal selfsupervised pre-training method for neural …
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Learning from Weak Supervision: Theory, Methods, and Applications
… models has driven widespread adoption of weak supervision and synthetic data methods, which use automated models instead of humans for annotation. Large language models (LLMs) have further accelerated this trend because their zero- and few-shot classification performance enables them to …
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Learning with Weak Supervision for Land Cover Mapping Problems
… that only rely on exact labeled data (strong supervision) have limited performance. This thesis investigates the use of weak supervision to mitigate the problem of not having sufficient samples with exact labels. In a weakly-supervised learning scenario, you have very few training samples that …
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Learning with Incidental Supervision
… provides hints sufficient to induce high quality supervision and utilizing these hints can be substantially less labor intensive than producing explicit annotation. This thesis introduces a framework we call Learning with Incidental Supervision, which formalizes these concepts. In particular, we …
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Learning Language with Multimodal Models
… neural language models require far more data and supervision, struggle with generalizing to new domains and overwhelmingly learn from text alone. This thesis explores how knowledge about child language acquisition – particularly the scale and type of linguistic information children receive, how …
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On Disentangled Analysis-by-Synthesis Shape Representations
… process. This provides several advantages: weak supervision, via the reconstructive signal, and the opportunity for disentanglement, via regularizing priors. The resulting representations are more versatile, controllable, and widely applicable. We begin by defining a prior on the deformation …
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Human Mesh Recovery Using Radio Signals
… challenge using: 1) a combination of strong and weak supervision, 2) a multi-headed self-attention mechanism that attends differently to temporal information in the radio signal, and 3) an adversarially trained temporal discriminator that imposes a prior on the dynamics of human motion. Our …
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Weakly Supervised Machine Learning for Cyberbullying Detection
… machine-learning framework that only requires weak supervision. We propose a general framework that trains an ensemble of two learners in which each learner looks at the problem from a different perspective. One learner identifies bullying incidents by examining the language content in the …
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Weakly-supervised text classification
… applications. Although many semi-supervised and weakly-supervised text classification models exist, they cannot be easily applied to deep neural models and meanwhile support limited supervision types. In this work, we propose a weakly-supervised framework that addresses the lack of training data …
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Classifying GitHub repositories with minimal human efforts
… framework to classify GitHub repositories under weak supervision. Three key modules, heterogeneous network construction and embedding, keyword extraction and topic modeling, as well as pseudo document generation, are used to tackle the above three challenges, respectively. We conduct extensive …
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Efficient Information Extraction Using Statistical Relational Learning
… this problem by employing some form of distant supervision. In this work, we take a different approach -- we create weakly supervised examples for relations by using commonsense knowledge. The key innovation is that this commonsense knowledge is completely independent of the natural language …
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Mining social media stimulus from news article text using weakly-supervised narrative classification
… dataset, which stops us from using existing weakly supervised text classification methods that heavily depend on class name semantics. 3) The noisy news article dataset: the collected dataset does not guarantee the documents will belong to any of the narratives. In such cases, the power of …
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Spoken ObjectNet: Creating a Bias-Controlled Spoken Caption Dataset
… to learn cross-modal correspondences with very weak supervision. However, modern audio-visual datasets contain biases that undermine the real-world performance of models trained on that data. We introduce Spoken ObjectNet, which is designed to remove some of these biases and provide a way to …
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Computational Models for the Automatic Learning and Recognition of Irish Sign Language
… movement epenthesis modeling and automatic or weakly supervised training have not been fully addressed in a single recognition framework. This work presents three main contributions in order to address these issues. The first contribution is a technique for user independent hand posture …
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Unmasking The Language Of Science Through Textual Analyses On Biomedical Preprints And Published Papers
… for our approach. In Chapter 4, we use the weak supervision paradigm to examine the possibility of speeding up the labeling function generation process for multiple biomedical relationship types. We found that the language used to describe a biomedical relationship is often distinct, leading …
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Text cube: construction, summarization and mining
… the given (label) name of each cube dimension as weak supervision. With such weak supervision, we develop a \emph{dimension-aware joint embedding} framework that learns joint representations for terms, documents, and labels. In the joint embedding process, our method iteratively learns …
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Language-Guided Video Understanding with Foundation Models
… scenarios remains limited by assumptions about supervision, training data availability, and offline access to complete video sequences. These constraints are particularly restrictive in settings such as surveillance and procedural assistance, where data is scarce, privacy-sensitive, and …
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