6 citations · 16 across the 10 of their papers we have counts for
10 papers
COOLIO: A Language Support Extension for the Classroom Object Oriented Language
Linhan Li, ThanhVu Nguyen
COOL is an Object-Oriented programming language used to teach compiler design in many undergraduate and graduate courses. Because most students are unfamiliar with the language and…
Implicit Regularization for Group Sparsity
Jiangyuan Li, Thanh V. Nguyen, Chinmay Hegde +1
We study the implicit regularization of gradient descent towards structured sparsity via a novel neural reparameterization, which we call a diagonally grouped linear neural network…
vieCap4H-VLSP 2021: Vietnamese Image Captioning for Healthcare Domain using Swin Transformer and Attention-based LSTM
Thanh Tin Nguyen, Long H. Nguyen, Nhat Truong Pham +4
This study presents our approach on the automatic Vietnamese image captioning for healthcare domain in text processing tasks of Vietnamese Language and Speech Processing (VLSP) Cha…
Example-based Explanations with Adversarial Attacks for Respiratory Sound Analysis
Yi Chang, Zhao Ren, Thanh Tam Nguyen +2
Respiratory sound classification is an important tool for remote screening of respiratory-related diseases such as pneumonia, asthma, and COVID-19. To facilitate the interpretabili…
Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis
Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde
A remarkable recent discovery in machine learning has been that deep neural networks can achieve impressive performance (in terms of both lower training error and higher generaliza…
BUZz: BUffer Zones for defending adversarial examples in image classification
Kaleel Mahmood, Phuong Ha Nguyen, Lam M. Nguyen +2
We propose a novel defense against all existing gradient based adversarial attacks on deep neural networks for image classification problems. Our defense is based on a combination…
Autoencoders Learn Generative Linear Models
Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde
We provide a series of results for unsupervised learning with autoencoders. Specifically, we study shallow two-layer autoencoder architectures with shared weights. We focus on thre…
On Learning Sparsely Used Dictionaries from Incomplete Samples
Thanh V. Nguyen, Akshay Soni, Chinmay Hegde
Most existing algorithms for dictionary learning assume that all entries of the (high-dimensional) input data are fully observed. However, in several practical applications (such a…
Provably Accurate Double-Sparse Coding
Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde
Sparse coding is a crucial subroutine in algorithms for various signal processing, deep learning, and other machine learning applications. The central goal is to learn an overcompl…
A Forward-Backward Approach for Visualizing Information Flow in Deep Networks
Aditya Balu, Thanh V. Nguyen, Apurva Kokate +2
We introduce a new, systematic framework for visualizing information flow in deep networks. Specifically, given any trained deep convolutional network model and a given test image,…