activity
20182020
most citedDistortion Agnostic Deep Watermarking

5 citations · 11 across the 4 of their papers we have counts for

collaborators

7 papers

eess.IV20204 cited

The Rate-Distortion-Accuracy Tradeoff: JPEG Case Study

Xiyang Luo, Hossein Talebi, Feng Yang +2

Handling digital images is almost always accompanied by a lossy compression in order to facilitate efficient transmission and storage. This introduces an unavoidable tension betwee…

eess.IV2020

GIFnets: Differentiable GIF Encoding Framework

Innfarn Yoo, Xiyang Luo, Yilin Wang +2

Graphics Interchange Format (GIF) is a widely used image file format. Due to the limited number of palette colors, GIF encoding often introduces color banding artifacts. Traditiona…

cs.MM20205 cited

Distortion Agnostic Deep Watermarking

Xiyang Luo, Ruohan Zhan, Huiwen Chang +2

Watermarking is the process of embedding information into an image that can survive under distortions, while requiring the encoded image to have little or no perceptual difference…

cs.LG20192 cited

A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting

Zhijian Li, Xiyang Luo, Bao Wang +2

We study epidemic forecasting on real-world health data by a graph-structured recurrent neural network (GSRNN). We achieve state-of-the-art forecasting accuracy on the benchmark CD…

cs.IR2018

Seq2Slate: Re-ranking and Slate Optimization with RNNs

Irwan Bello, Sayali Kulkarni, Sagar Jain +6

Ranking is a central task in machine learning and information retrieval. In this task, it is especially important to present the user with a slate of items that is appealing as a w…

cs.LG2018

Constrained Classification and Ranking via Quantiles

Alan Mackey, Xiyang Luo, Elad Eban

In most machine learning applications, classification accuracy is not the primary metric of interest. Binary classifiers which face class imbalance are often evaluated by the