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- research-articleMarch 2024
Conditional Generative Adversarial Network for Early Classification of Longitudinal Datasets Using an Imputation Approach
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 5Article No.: 132, Pages 1–25https://doi.org/10.1145/3644821Early classification of longitudinal data remains an active area of research today. The complexity of these datasets and the high rates of missing data caused by irregular sampling present data-level challenges for the Early Longitudinal Data ...
- ArticleFebruary 2024
Physics-Aware Machine Learning for Dynamic, Data-Driven Radar Target Recognition
AbstractDespite advances in Artificial Intelligence and Machine Learning (AI/ML) for automatic target recognition (ATR) using surveillance radar, there remain significant challenges to robust and accurate perception in operational environments. Physics-...
- research-articleAugust 2022
AL-PA: cross-device profiled side-channel attack using adversarial learning
DAC '22: Proceedings of the 59th ACM/IEEE Design Automation ConferencePages 691–696https://doi.org/10.1145/3489517.3530517In this paper, we focus on the portability issue in profiled side-channel attacks (SCAs) that arises due to significant device-to-device variations. Device discrepancy is inevitable in realistic attacks, but it is often neglected in research works. In ...
- research-articleJune 2022
NFTGAN: Non-Fungible Token Art Generation Using Generative Adversarial Networks
ICMLT '22: Proceedings of the 2022 7th International Conference on Machine Learning TechnologiesPages 255–259https://doi.org/10.1145/3529399.3529439Digital arts have gained an unprecedented level of popularity with the emergence of non-fungible tokens (NFTs). NFTs are cryptographic assets that are stored on blockchain networks and represent a digital certificate of ownership that cannot be forged. ...
- short-paperOctober 2021
Adversarial Domain Adaptation for Cross-lingual Information Retrieval with Multilingual BERT
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge ManagementPages 3498–3502https://doi.org/10.1145/3459637.3482050Transformer-based language models (e.g. BERT, RoBERT, GPT, etc) have shown remarkable performance in many natural language processing tasks and their multilingual variants make it easier to handle cross-lingual tasks without using machine translation ...
- research-articleJune 2021
Unsupervised Lifelong Learning with Curricula
WWW '21: Proceedings of the Web Conference 2021Pages 3534–3545https://doi.org/10.1145/3442381.3449839Lifelong machine learning (LML) has driven the development of extensive web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned ...
- research-articleOctober 2020
IR-GAN: Image Manipulation with Linguistic Instruction by Increment Reasoning
MM '20: Proceedings of the 28th ACM International Conference on MultimediaPages 322–330https://doi.org/10.1145/3394171.3413777Conditional image generation is an active research topic including text2image and image translation. Recently image manipulation with linguistic instruction brings new challenges of multimodal conditional generation. However, traditional conditional ...
- research-articleJanuary 2020
Paraphrase identification using collaborative adversarial networks
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology (JIFS), Volume 39, Issue 1Pages 1021–1032https://doi.org/10.3233/JIFS-191933The paper presents a Collaborative Adversarial Network (CAN) model for paraphrase identification, which is a collaborative network holding generator that is pitted against an adversarial network called discriminator. There has been tremendous research ...
- research-articleOctober 2018
Learning Joint Multimodal Representation with Adversarial Attention Networks
MM '18: Proceedings of the 26th ACM international conference on MultimediaPages 1874–1882https://doi.org/10.1145/3240508.3240614Recently, learning a joint representation for the multimodal data (e.g., containing both visual content and text description) has attracted extensive research interests. Usually, the features of different modalities are correlational and compositive, ...
- research-articleJuly 2018
Learning Adversarial Networks for Semi-Supervised Text Classification via Policy Gradient
KDD '18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningPages 1715–1723https://doi.org/10.1145/3219819.3219956Semi-supervised learning is a branch of machine learning techniques that aims to make fully use of both labeled and unlabeled instances to improve the prediction performance. The size of modern real world datasets is ever-growing so that acquiring label ...
- research-articleApril 2018
Minimizing Queue Length Regret Under Adversarial Network Models
Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), Volume 2, Issue 1Article No.: 11, Pages 1–32https://doi.org/10.1145/3179414Stochastic models have been dominant in network optimization theory for over two decades, due to their analytical tractability. However, these models fail to capture non-stationary or even adversarial network dynamics which are of increasing importance ...
- research-articleAugust 2017
Learning to Generate High Resolution Images with Bilateral Adversarial Networks
ICAIP '17: Proceedings of the International Conference on Advances in Image ProcessingPages 113–117https://doi.org/10.1145/3133264.3133289Learning the generative models of multimedia data such as audio, images and video is a challenging image analysis problem because of the infinitely many manifestations of just one concept, and the potentially large number of concepts that can be ...