1 code implementation • ICML 2020 • Thomas Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
Interpretability allows the domain-expert to directly evaluate the model's relevance and reliability, a practice that offers assurance and builds trust.
no code implementations • SemEval (NAACL) 2022 • Dang Nguyen, Huy Khac Nguyen Huynh
In this paper, we describe a system that we built to participate in the SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition, specifically the track Mono-lingual in English.
no code implementations • 27 Apr 2024 • Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman
Can we modify the training data distribution to encourage the underlying optimization method toward finding solutions with superior generalization performance on in-distribution data?
no code implementations • 26 Feb 2024 • Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta
When the function is black-box and expensive to evaluate, the level sets need to be found in a minimum set of function evaluations.
no code implementations • 5 Feb 2024 • Kien Do, Dung Nguyen, Hung Le, Thao Le, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh
To overcome this challenge, we propose to approximate \frac{1}{p(u|b)} using a biased classifier trained with "bias amplification" losses.
no code implementations • 5 Feb 2024 • Kien Do, Duc Kieu, Toan Nguyen, Dang Nguyen, Hung Le, Dung Nguyen, Thin Nguyen
We introduce "posterior flows" - generalizations of "probability flows" to a broader class of stochastic processes not necessarily diffusion processes - and propose a systematic training-free method to transform the posterior flow of a "linear" stochastic process characterized by the equation Xt = at * X0 + st * X1 into a straight constant-speed (SC) flow, reminiscent of Rectified Flow.
1 code implementation • 28 Nov 2023 • Dang Nguyen, Chacha Chen, He He, Chenhao Tan
When pneumonia is not found on a chest X-ray, should the report describe this negative observation or omit it?
no code implementations • 1 Nov 2023 • Dang Nguyen, Phat K. Huynh, Vinh Duc An Bui, Kee Young Hwang, Nityanand Jain, Chau Nguyen, Le Huu Nhat Minh, Le Van Truong, Xuan Thanh Nguyen, Dinh Hoang Nguyen, Le Tien Dung, Trung Q. Le, Manh-Huong Phan
In this work, we fused magnetic respiratory sensing technology (MRST) with machine learning (ML) to create a diagnostic platform for real-time tracking and diagnosis of COVID-19 and other respiratory diseases.
no code implementations • 8 Oct 2023 • Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman
Recently, multimodal contrastive learning (MMCL) approaches, such as CLIP, have achieved a remarkable success in learning representations that are robust against distribution shift and generalize to new domains.
1 code implementation • 12 Jan 2023 • Khai Nguyen, Dang Nguyen, Nhat Ho
Despite being efficient, Max-SW and its amortized version cannot guarantee metricity property due to the sub-optimality of the projected gradient ascent and the amortization gap.
no code implementations • 21 Sep 2022 • Kien Do, Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh
Since the EMA generator can be considered as an ensemble of the generator's old versions and often undergoes a smaller change in updates compared to the generator, training on its synthetic samples can help the student recall the past knowledge and prevent the student from adapting too quickly to new updates of the generator.
1 code implementation • 25 Jul 2022 • Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh
Traditional KD methods require lots of labeled training samples and a white-box teacher (parameters are accessible) to train a good student.
1 code implementation • 25 Jul 2022 • Azhar Mohammed, Dang Nguyen, Bao Duong, Thin Nguyen
Data augmentation is one of the most successful techniques to improve the classification accuracy of machine learning models in computer vision.
no code implementations • 13 May 2022 • Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh
We introduce a conditional compression problem and propose a fast framework for tackling it.
no code implementations • 24 Feb 2022 • Kien Do, Haripriya Harikumar, Hung Le, Dung Nguyen, Truyen Tran, Santu Rana, Dang Nguyen, Willy Susilo, Svetha Venkatesh
Trojan attacks on deep neural networks are both dangerous and surreptitious.
no code implementations • 29 Oct 2021 • Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho
To address this issue, we propose a novel model fusion framework, named CLAFusion, to fuse neural networks with a different number of layers, which we refer to as heterogeneous neural networks, via cross-layer alignment.
2 code implementations • 22 Aug 2021 • Khai Nguyen, Dang Nguyen, The-Anh Vu-Le, Tung Pham, Nhat Ho
Mini-batch optimal transport (m-OT) has been widely used recently to deal with the memory issue of OT in large-scale applications.
no code implementations • 7 Jul 2021 • Quan Duong, Dang Nguyen, Quoc Nguyen
This study aims to propose effective modeling and approach for designing a logistics network in the urban area in order to offer an efficient flow distribution network as a competitive strategy in the logistics industry where demand is sensitive to both price and time.
2 code implementations • 11 Feb 2021 • Khai Nguyen, Dang Nguyen, Quoc Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho
To address these problems, we propose a novel mini-batch scheme for optimal transport, named Batch of Mini-batches Optimal Transport (BoMb-OT), that finds the optimal coupling between mini-batches and it can be seen as an approximation to a well-defined distance on the space of probability measures.
no code implementations • 19 Jun 2020 • Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
In real-world applications, BO often faces a major problem of missing values in inputs.
1 code implementation • 2 Jun 2020 • Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
We define personalized interpretability as a measure of sample-specific feature attribution, and view it as a minimum requirement for a precision health model to justify its conclusions.
1 code implementation • 28 Nov 2019 • Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
To optimize such functions, we propose a new method that formulates the problem as a multi-armed bandit problem, wherein each category corresponds to an arm with its reward distribution centered around the optimum of the objective function in continuous variables.
no code implementations • 21 Feb 2019 • Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen
In this paper we consider the problem of finding stable maxima of expensive (to evaluate) functions.
no code implementations • SEMEVAL 2017 • Khoa Nguyen, Dang Nguyen
This paper describes the improvements that we have applied on CAMR baseline parser (Wang et al., 2016) at Task 8 of SemEval-2016.
no code implementations • 2 Dec 2016 • Dang Nguyen, Wei Luo, Dinh Phung, Svetha Venkatesh
In this paper, we consider the patient similarity matching problem over a cancer cohort of more than 220, 000 patients.