1 code implementation • 7 Dec 2023 • Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh
Recent data-privacy laws have sparked interest in machine unlearning, which involves removing the effect of specific training samples from a learnt model as if they were never present in the original training dataset.
no code implementations • 27 Oct 2022 • Cuong Pham, Tuan Hoang, Thanh-Toan Do
Knowledge distillation which learns a lightweight student model by distilling knowledge from a cumbersome teacher model is an attractive approach for learning compact deep neural networks (DNNs).
no code implementations • 13 Dec 2021 • Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen, Ngai-Man Cheung
First, to learn informative representations that can preserve both intra- and inter-modal similarities, we leverage the recent advances in estimating variational lower-bound of MI to maximize the MI between the binary representations and input features and between binary representations of different modalities.
no code implementations • 26 Dec 2020 • Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen, Ngai-Man Cheung
With this approach, we can learn activation quantizers that minimize the quantization errors in the majority of channels.
no code implementations • 1 Aug 2020 • Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen, Ngai-Man Cheung
This paper presents a novel framework, namely Deep Cross-modality Spectral Hashing (DCSH), to tackle the unsupervised learning problem of binary hash codes for efficient cross-modal retrieval.
no code implementations • 27 Jun 2019 • Huu Le, Tuan Hoang, Michael Milford
Visual localization algorithms have achieved significant improvements in performance thanks to recent advances in camera technology and vision-based techniques.
no code implementations • 24 Apr 2019 • Thanh-Toan Do, Khoa Le, Tuan Hoang, Huu Le, Tam V. Nguyen, Ngai-Man Cheung
This global vector is then subjected to a hashing function to generate a binary hash code.
no code implementations • CVPR 2019 • Thanh-Toan Do, Toan Tran, Ian Reid, Vijay Kumar, Tuan Hoang, Gustavo Carneiro
Another approach explored in the field relies on an ad-hoc linearization (in terms of N) of the triplet loss that introduces class centroids, which must be optimized using the whole training set for each mini-batch - this means that a naive implementation of this approach has run-time complexity O(N^2).
1 code implementation • 6 Apr 2019 • Huu Le, Thanh-Toan Do, Tuan Hoang, Ngai-Man Cheung
In particular, our work enables the use of randomized methods for point cloud registration without the need of putative correspondences.
no code implementations • 5 Feb 2019 • Huu Le, Tuan Hoang, Qianggong Zhang, Thanh-Toan Do, Anders Eriksson, Michael Milford
In this paper, we present a novel 6-DOF localization system that for the first time simultaneously achieves all the three characteristics: significantly sub-linear storage growth, agnosticism to image descriptors, and customizability to available storage and computational resources.
no code implementations • 21 Feb 2018 • Thanh-Toan Do, Tuan Hoang, Dang-Khoa Le Tan, Trung Pham, Huu Le, Ngai-Man Cheung, Ian Reid
However, training deep hashing networks for the task is challenging due to the binary constraints on the hash codes, the similarity preserving property, and the requirement for a vast amount of labelled images.
no code implementations • 19 Feb 2018 • Tuan Hoang, Thanh-Toan Do, Huu Le, Dang-Khoa Le-Tan, Ngai-Man Cheung
For unsupervised data-dependent hashing, the two most important requirements are to preserve similarity in the low-dimensional feature space and to minimize the binary quantization loss.
1 code implementation • 7 Feb 2018 • Thanh-Toan Do, Tuan Hoang, Dang-Khoa Le Tan, Huu Le, Tam V. Nguyen, Ngai-Man Cheung
In the large-scale image retrieval task, the two most important requirements are the discriminability of image representations and the efficiency in computation and storage of representations.
no code implementations • 8 Dec 2017 • Thanh-Toan Do, Tuan Hoang, Dang-Khoa Le Tan, Anh-Dzung Doan, Ngai-Man Cheung
This design has overcome a challenging problem in some previous works: optimizing non-smooth objective functions because of binarization.
1 code implementation • 4 Jul 2017 • Tuan Hoang, Thanh-Toan Do, Dang-Khoa Le Tan, Ngai-Man Cheung
Recent work adopts fine-tuned strategies to further improve the discriminative power of the descriptors.
no code implementations • 6 Apr 2017 • Tuan Hoang, Thanh-Toan Do, Dang-Khoa Le Tan, Ngai-Man Cheung
We introduce a novel approach to improve unsupervised hashing.