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08/15/2023
Improved Region Proposal Network for Enhanced Few-Shot Object Detection
Despite significant success of deep learning in object detection tasks, ...
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05/30/2023
History Repeats: Overcoming Catastrophic Forgetting For Event-Centric Temporal Knowledge Graph Completion
Temporal knowledge graph (TKG) completion models typically rely on havin...
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05/28/2023
Cognitively Inspired Cross-Modal Data Generation Using Diffusion Models
Most existing cross-modal generative methods based on diffusion models u...
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04/05/2023
Low-Shot Learning for Fictional Claim Verification
In this paper, we study the problem of claim verification in the context...
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04/04/2023
I2I: Initializing Adapters with Improvised Knowledge
Adapters present a promising solution to the catastrophic forgetting pro...
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03/26/2023
Explainable Artificial Intelligence Architecture for Melanoma Diagnosis Using Indicator Localization and Self-Supervised Learning
Melanoma is a prevalent lethal type of cancer that is treatable if diagn...
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03/25/2023
Task-Attentive Transformer Architecture for Continual Learning of Vision-and-Language Tasks Using Knowledge Distillation
The size and the computational load of fine-tuning large-scale pre-train...
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03/22/2023
Unsupervised Domain Adaptation for Training Event-Based Networks Using Contrastive Learning and Uncorrelated Conditioning
Event-based cameras offer reliable measurements for preforming computer ...
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03/22/2023
Encoding Binary Concepts in the Latent Space of Generative Models for Enhancing Data Representation
Binary concepts are empirically used by humans to generalize efficiently...
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03/18/2023
Identification of Novel Classes for Improving Few-Shot Object Detection
Conventional training of deep neural networks requires a large number of...
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01/29/2023
Preserving Fairness in AI under Domain Shift
Existing algorithms for ensuring fairness in AI use a single-shot traini...
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01/29/2023
Unsupervised Domain Adaptation for Graph-Structured Data Using Class-Conditional Distribution Alignment
Adopting deep learning models for graph-structured data is challenging d...
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11/02/2022
Unsupervised Model Adaptation for Source-free Segmentation of Medical Images
The recent prevalence of deep neural networks has lead semantic segmenta...
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09/29/2022
Increasing Model Generalizability for Unsupervised Domain Adaptation
A dominant approach for addressing unsupervised domain adaptation is to ...
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07/10/2022
Automating Detection of Papilledema in Pediatric Fundus Images with Explainable Machine Learning
Papilledema is an ophthalmic neurologic disorder in which increased intr...
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06/18/2022
CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks
Current state-of-the-art vision-and-language models are evaluated on tas...
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10/09/2021
Cognitively Inspired Learning of Incremental Drifting Concepts
Humans continually expand their learned knowledge to new domains and lea...
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08/27/2021
Detection and Continual Learning of Novel Face Presentation Attacks
Advances in deep learning, combined with availability of large datasets,...
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07/04/2021
Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation
Sentiment analysis is a costly yet necessary task for enterprises to stu...
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06/23/2021
Secure Domain Adaptation with Multiple Sources
Multi-source unsupervised domain adaptation (MUDA) is a recently explore...
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04/18/2021
Lifelong Learning of Few-shot Learners across NLP Tasks
Recent advances in large pre-trained language models have greatly improv...
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01/02/2021
Privacy Preserving Domain Adaptation for Semantic Segmentation of Medical Images
Convolutional neural networks (CNNs) have led to significant improvement...
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09/26/2020
Unsupervised Model Adaptation for Continual Semantic Segmentation
We develop an algorithm for adapting a semantic segmentation model that ...
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07/01/2020
Sequential Unsupervised Domain Adaptation through Prototypical Distributions
We develop an algorithm for unsupervised domain adaptation (UDA) of a cl...
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07/04/2019
Learning a Domain-Invariant Embedding for Unsupervised Domain Adaptation Using Class-Conditioned Distribution Alignment
We address the problem of unsupervised domain adaptation (UDA) by learni...
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06/10/2019
Generative Continual Concept Learning
After learning a concept, humans are also able to continually generalize...
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03/11/2019
Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay
Despite huge success, deep networks are unable to learn effectively in s...
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10/10/2017
Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer
Knowledge transfer between tasks can improve the performance of learned ...
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09/12/2017
Joint Dictionaries for Zero-Shot Learning
A classic approach toward zero-shot learning (ZSL) is to map the input d...
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03/22/2016
Image Super-Resolution Based on Sparsity Prior via Smoothed l_0 Norm
In this paper we aim to tackle the problem of reconstructing a high-reso...
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03/08/2016