11 citations · 18 across the 4 of their papers we have counts for
7 papers
Asymmetric Hashing for Fast Ranking via Neural Network Measures
Khoa Doan, Shulong Tan, Weijie Zhao +1
Fast item ranking is an important task in recommender systems. In previous works, graph-based Approximate Nearest Neighbor (ANN) approaches have demonstrated good performance on it…
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class
Khoa D. Doan, Yingjie Lao, Ping Li
In recent years, machine learning models have been shown to be vulnerable to backdoor attacks. Under such attacks, an adversary embeds a stealthy backdoor into the trained model su…
One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional Matching
Khoa D. Doan, Peng Yang, Ping Li
Image hashing is a principled approximate nearest neighbor approach to find similar items to a query in a large collection of images. Hashing aims to learn a binary-output function…
Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space
Khoa D. Doan, Saurav Manchanda, Fengjiao Wang +3
For a given image generation problem, the intrinsic image manifold is often low dimensional. We use the intuition that it is much better to train the GAN generator by minimizing th…
Regression via Implicit Models and Optimal Transport Cost Minimization
Saurav Manchanda, Khoa Doan, Pranjul Yadav +1
This paper addresses the classic problem of regression, which involves the inductive learning of a map, , denoting noise, $f:\mathbb{R}^n\times \mathbb{R}^k \rightarr…
Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
Khoa D. Doan, Saurav Manchanda, Sarkhan Badirli +1
Image hashing is one of the fundamental problems that demand both efficient and effective solutions for various practical scenarios. Adversarial autoencoders are shown to be able t…