146 citations · 646 across the 40 of their papers we have counts for
8 papers · 1 filter
Differentially Private Synthetic Medical Data Generation using Convolutional GANs
Amirsina Torfi, Edward A. Fox, Chandan K. Reddy
Deep learning models have demonstrated superior performance in several application problems, such as image classification and speech processing. However, creating a deep learning m…
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs
Nurendra Choudhary, Nikhil Rao, Sumeet Katariya +2
Knowledge Graphs (KGs) are ubiquitous structures for information storagein several real-world applications such as web search, e-commerce, social networks, and biology. Querying KG…
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment Analysis
Tian Shi, Ping Wang, Chandan K. Reddy
In recent years, several online platforms have seen a rapid increase in the number of review systems that request users to provide aspect-level feedback. Document-level Multi-aspec…
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection
Tian Shi, Liuqing Li, Ping Wang +1
Unsupervised aspect detection (UAD) aims at automatically extracting interpretable aspects and identifying aspect-specific segments (such as sentences) from online reviews. However…
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
Ping Wang, Khushbu Agarwal, Colby Ham +2
Representation learning methods for heterogeneous networks produce a low-dimensional vector embedding for each node that is typically fixed for all tasks involving the node. Many o…
Corpus-level and Concept-based Explanations for Interpretable Document Classification
Tian Shi, Xuchao Zhang, Ping Wang +1
Using attention weights to identify information that is important for models' decision-making is a popular approach to interpret attention-based neural networks. This is commonly r…
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…
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…