no code implementations • 12 Aug 2014 • Vu Dinh, Lam Si Tung Ho, Nguyen Viet Cuong, Duy Nguyen, Binh T. Nguyen
We prove new fast learning rates for the one-vs-all multiclass plug-in classifiers trained either from exponentially strongly mixing data or from data generated by a converging drifting distribution.
no code implementations • NeurIPS 2016 • Vu Dinh, Lam Si Tung Ho, Duy Nguyen, Binh T. Nguyen
We study fast learning rates when the losses are not necessarily bounded and may have a distribution with heavy tails.
no code implementations • 5 Feb 2018 • Duy H. M. Nguyen, Duy M. Nguyen, Mai T. N. Truong, Thu Nguyen, Khanh T. Tran, Nguyen A. Triet, Pham T. Bao, Binh T. Nguyen
Brain extraction (skull stripping) is a challenging problem in neuroimaging.
no code implementations • 23 Sep 2020 • Duy M. H. Nguyen, Duy M. Nguyen, Huong Vu, Binh T. Nguyen, Fabrizio Nunnari, Daniel Sonntag
Until now, Coronavirus SARS-CoV-2 has caused more than 850, 000 deaths and infected more than 27 million individuals in over 120 countries.
1 code implementation • 23 Sep 2020 • Thu Nguyen, Duy H. M. Nguyen, Huy Nguyen, Binh T. Nguyen, Bruce A. Wade
The problem of monotone missing data has been broadly studied during the last two decades and has many applications in different fields such as bioinformatics or statistics.
3 code implementations • 30 Dec 2020 • Ha Q. Nguyen, Khanh Lam, Linh T. Le, Hieu H. Pham, Dat Q. Tran, Dung B. Nguyen, Dung D. Le, Chi M. Pham, Hang T. T. Tong, Diep H. Dinh, Cuong D. Do, Luu T. Doan, Cuong N. Nguyen, Binh T. Nguyen, Que V. Nguyen, Au D. Hoang, Hien N. Phan, Anh T. Nguyen, Phuong H. Ho, Dat T. Ngo, Nghia T. Nguyen, Nhan T. Nguyen, Minh Dao, Van Vu
Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs.
no code implementations • 4 Apr 2021 • Duy M. H. Nguyen, Thu T. Nguyen, Huong Vu, Quang Pham, Manh-Duy Nguyen, Binh T. Nguyen, Daniel Sonntag
Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task.
no code implementations • 31 May 2021 • Binh T. Nguyen, Duy M. Nguyen, Lam Si Tung Ho, Vu Dinh
In this work, we introduce a novel method for solving the set inversion problem by formulating it as a binary classification problem.
1 code implementation • 4 Jun 2021 • Manh-Duy Nguyen, Binh T. Nguyen, Cathal Gurrin
In this paper, we introduce the Local and Global Scene Graph Matching (LGSGM) model that enhances the state-of-the-art method by integrating an extra graph convolution network to capture the general information of a graph.
Ranked #4 on Image Retrieval on Flickr30K 1K test
1 code implementation • 6 Jun 2021 • Thu Nguyen, Khoi Minh Nguyen-Duy, Duy Ho Minh Nguyen, Binh T. Nguyen, Bruce Alan Wade
The missing data problem has been broadly studied in the last few decades and has various applications in different areas such as statistics or bioinformatics.
1 code implementation • 18 Jun 2021 • Hieu Tran, Long Phan, James Anibal, Binh T. Nguyen, Truong-Son Nguyen
In this paper, we propose SPBERT, a transformer-based language model pre-trained on massive SPARQL query logs.
1 code implementation • IEA/AIE 2021 • Hieu Tran, Cuong V. Dinh, Quang Pham, Binh T. Nguyen
In both formal and informal texts, missing punctuation marks make the texts confusing and challenging to read.
1 code implementation • 26 Jul 2021 • Hieu T. Ung, Huy Q. Ung, Binh T. Nguyen
Accurate insect pest recognition is significant to protect the crop or take the early treatment on the infected yield, and it helps reduce the loss for the agriculture economy.
1 code implementation • 4 Aug 2021 • Boi M. Quach, Dinh V. Cuong, Nhung Pham, Dang Huynh, Binh T. Nguyen
In recent years, there is a considerable increase in the number of studies related to plant taxonomy.
1 code implementation • 21 Oct 2021 • Cuong V. Nguyen, Tien-Dung Cao, Tram Truong-Huu, Khanh N. Pham, Binh T. Nguyen
In this paper, we perform an empirical study on the impact of several loss functions on the performance of standard GAN models, Deep Convolutional Generative Adversarial Networks (DCGANs).
no code implementations • 19 Nov 2021 • Lam Si Tung Ho, Binh T. Nguyen, Vu Dinh, Duy Nguyen
We prove that under the multi-scale Bernstein's condition, the generalized posterior distribution concentrates around the set of optimal hypotheses and the generalized Bayes estimator can achieve fast learning rate.
no code implementations • 18 Mar 2022 • Van-Tu Ninh, Manh-Duy Nguyen, Sinéad Smyth, Minh-Triet Tran, Graham Healy, Binh T. Nguyen, Cathal Gurrin
Using our proposed model architecture, we compare the accuracy between stress detection models that use measures from each individual signal source, and one model employing the fusion of multiple sensor sources.
no code implementations • 12 May 2022 • Quynh Nguyen, Dac H. Nguyen, Son T. Huynh, Hoa K. Dam, Binh T. Nguyen
This paper proposes an efficient task dependency recommendation algorithm to suggest tasks dependent on a given task that the user has just created.
no code implementations • 12 May 2022 • Son T. Huynh, Nhi Dang, Dac H. Nguyen, Phong T. Huynh, Binh T. Nguyen
Recommender systems have been increasingly popular in entertainment and consumption and are evident in academics, especially for applications that suggest submitting scientific articles to scientists.
1 code implementation • 12 May 2022 • Duc H. Le, Tram T. Doan, Son T. Huynh, Binh T. Nguyen
This study suggests a more advanced method for enhancing the efficiency of the paper submission recommendation system compared to previous approaches when we respectively achieve 0. 5173, 0. 8097, 0. 8862, 0. 9496 for Top 1, 3, 5, and 10 accuracies on the test set for combining the title, abstract, and keywords as input features.
no code implementations • 12 May 2022 • Thao V. Ha, Hoang Nguyen, Son T. Huynh, Trung T. Nguyen, Binh T. Nguyen
In recent years, the occurrence of falls has increased and has had detrimental effects on older adults.
1 code implementation • 26 May 2022 • Thu Nguyen, Quang M. Le, Son N. T. Tu, Binh T. Nguyen
Fisher Discriminant Analysis (FDA) is one of the essential tools for feature extraction and classification.
no code implementations • 29 May 2022 • Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot
Identifying the relevant variables for a classification model with correct confidence levels is a central but difficult task in high-dimension.
3 code implementations • 27 Jun 2022 • Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré La Tour, Ghislain Durif, Cassio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoit Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
Numerical validation is at the core of machine learning research as it allows to assess the actual impact of new methods, and to confirm the agreement between theory and practice.
1 code implementation • 26 Jul 2022 • Nhat L. Vu, Thanh P. Nguyen, Binh T. Nguyen, Vu Dinh, Lam Si Tung Ho
Reconstructing the ancestral state of a group of species helps answer many important questions in evolutionary biology.
no code implementations • 4 Dec 2022 • Duy M. H. Nguyen, Hoang Nguyen, Mai T. N. Truong, Tri Cao, Binh T. Nguyen, Nhat Ho, Paul Swoboda, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag
Recent breakthroughs in self-supervised learning (SSL) offer the ability to overcome the lack of labeled training samples by learning feature representations from unlabeled data.
no code implementations • 30 Dec 2022 • Hasan Md Tusfiqur, Duy M. H. Nguyen, Mai T. N. Truong, Triet A. Nguyen, Binh T. Nguyen, Michael Barz, Hans-Juergen Profitlich, Ngoc T. T. Than, Ngan Le, Pengtao Xie, Daniel Sonntag
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world, and early DR detection is necessary to prevent vision loss and support an appropriate treatment.
2 code implementations • 11 Jan 2023 • Manh-Duy Nguyen, Binh T. Nguyen, Cathal Gurrin
It is not easy to propose a new model with a novel architecture and intensively train it on a massive dataset with many GPUs to surpass many SOTA models, which are already available to use on the Internet.
1 code implementation • 2 Feb 2023 • Mai Anh Vu, Thu Nguyen, Tu T. Do, Nhan Phan, Nitesh V. Chawla, Pål Halvorsen, Michael A. Riegler, Binh T. Nguyen
Missing data frequently occurs in datasets across various domains, such as medicine, sports, and finance.
1 code implementation • 16 Mar 2023 • Cuong V. Nguyen, Khiem H. Le, Anh M. Tran, Quang H. Pham, Binh T. Nguyen
Transfer learning plays an essential role in Deep Learning, which can remarkably improve the performance of the target domain, whose training data is not sufficient.
1 code implementation • ICLR 2023 Tiny Paper Track 2023 • Khoi Minh Nguyen-Duy, Quang Pham, Binh T. Nguyen
Orthogonal parameterization is a compelling solution to the vanishing gradient problem (VGP) in recurrent neural networks (RNNs).
Ranked #15 on Sequential Image Classification on Sequential MNIST
no code implementations • 10 May 2023 • Nhat-Hao Pham, Khanh-Linh Vo, Mai Anh Vu, Thu Nguyen, Michael A. Riegler, Pål Halvorsen, Binh T. Nguyen
Correlation matrix visualization is essential for understanding the relationships between variables in a dataset, but missing data can pose a significant challenge in estimating correlation coefficients.
no code implementations • 10 May 2023 • Tu T. Do, Mai Anh Vu, Tuan L. Vo, Hoang Thien Ly, Thu Nguyen, Steven A. Hicks, Michael A. Riegler, Pål Halvorsen, Binh T. Nguyen
To address this issue, we propose a Blockwise principal component analysis Imputation (BPI) framework for dimensionality reduction and imputation of monotone missing data.
1 code implementation • NeurIPS 2023 • Duy M. H. Nguyen, Hoang Nguyen, Nghiem T. Diep, Tan N. Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert
While pre-trained deep networks on ImageNet and vision-language foundation models trained on web-scale data are prevailing approaches, their effectiveness on medical tasks is limited due to the significant domain shift between natural and medical images.
no code implementations • 9 Oct 2023 • Quan Huu Do, Binh T. Nguyen, Lam Si Tung Ho
Existing generalization bounds for deep neural networks require data to be independent and identically distributed (iid).
no code implementations • 18 Nov 2023 • Duy Minh Ho Nguyen, Tan Ngoc Pham, Nghiem Tuong Diep, Nghi Quoc Phan, Quang Pham, Vinh Tong, Binh T. Nguyen, Ngan Hoang Le, Nhat Ho, Pengtao Xie, Daniel Sonntag, Mathias Niepert
Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging.
no code implementations • 22 Dec 2023 • Junyu Chen, Binh T. Nguyen, Yong Sheng Soh
The Gromov-Wasserstein (GW) distance is a variant of the optimal transport problem that allows one to match objects between incomparable spaces.
no code implementations • 4 Feb 2024 • Quang Pham, Giang Do, Huy Nguyen, TrungTin Nguyen, Chenghao Liu, Mina Sartipi, Binh T. Nguyen, Savitha Ramasamy, XiaoLi Li, Steven Hoi, Nhat Ho
Sparse mixture of experts (SMoE) offers an appealing solution to scale up the model complexity beyond the mean of increasing the network's depth or width.