mlsanityData to 14 Oct 2026

Robust Internal Representations for Domain Generalization

arXiv 2309.15522 ↗First posted 27 Sep 2023cs.LG cs.AIcited by 0

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Abstract (arXiv)

This paper which is part of the New Faculty Highlights Invited Speaker Program of AAAI'23, serves as a comprehensive survey of my research in transfer learning by utilizing embedding spaces. The work reviewed in this paper specifically revolves around the inherent challenges associated with continual learning and limited availability of labeled data. By providing an overview of my past and ongoing contributions, this paper aims to present a holistic understanding of my research, paving the way for future explorations and advancements in the field. My research delves into the various settings of transfer learning, including, few-shot learning, zero-shot learning, continual learning, domain adaptation, and distributed learning. I hope this survey provides a forward-looking perspective for researchers who would like to focus on similar research directions.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 32 of its 65 references that are in the map. First posted on arXiv 27 Sep 2023.

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32 of 65 references.

References · 32

  1. 2022CLiMB: A Continual Learning Benchmark for Vision-and-Language Taskscited by 68
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  7. 2020Overcoming Concept Shift in Domain-Aware Settings through Consolidated Internal Distributionscited by 21
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  10. 2020One-shot Learning for Temporal Knowledge Graphscited by 14
  11. 2023Unsupervised Domain Adaptation for Training Event-Based Networks Using Contrastive Learning and Uncorrelated Conditioningcited by 14
  12. 2017Multi-Agent Distributed Lifelong Learning for Collective Knowledge Acquisitioncited by 13
20 more
  1. 2022Unsupervised Model Adaptation for Source-free Segmentation of Medical Imagescited by 13
  2. 2019Learning a Domain-Invariant Embedding for Unsupervised Domain Adaptation Using Class-Conditioned Distribution Alignmentcited by 12
  3. 2021Domain Adaptation for the Segmentation of Confidential Medical Imagescited by 12
  4. 2021Secure Domain Adaptation with Multiple Sourcescited by 12
  5. 2023Task-Attentive Transformer Architecture for Continual Learning of Vision-and-Language Tasks Using Knowledge Distillationcited by 11
  6. 2019Zero-Shot Image Classification Using Coupled Dictionary Embeddingcited by 10
  7. 2017Joint Dictionaries for Zero-Shot Learningcited by 9
  8. 2023Identification of Novel Classes for Improving Few-Shot Object Detectioncited by 7
  9. 2023I2I: Initializing Adapters with Improvised Knowledgecited by 7
  10. 2018Discovering Molecular Functional Groups Using Graph Convolutional Neural Networkscited by 5
  11. 2023History Repeats: Overcoming Catastrophic Forgetting For Event-Centric Temporal Knowledge Graph Completioncited by 5
  12. 2023Improved Region Proposal Network for Enhanced Few-Shot Object Detectioncited by 5
  13. 2021Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separationcited by 4
  14. 2016Testing fine-grained parallelism for the ADMM on a factor-graphcited by 3
  15. 2023Preserving Fairness in AI under Domain Shiftcited by 3
  16. 2022Automating Detection of Papilledema in Pediatric Fundus Images with Explainable Machine Learningcited by 2
  17. 2023Graph Harmony: Denoising and Nuclear-Norm Wasserstein Adaptation for Enhanced Domain Transfer in Graph-Structured Datacited by 2
  18. 2023Encoding Binary Concepts in the Latent Space of Generative Models for Enhancing Data Representationcited by 2
  19. 2023Explainable Artificial Intelligence Architecture for Melanoma Diagnosis Using Indicator Localization and Self-Supervised Learningcited by 2
  20. 2016Image Super-Resolution Based on Sparsity Prior via Smoothed l0 Normcited by 1

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