activity
20182022
most citedMemory Augmented Generative Adversarial Networks for Anomaly Detection

4 citations · 8 across the 3 of their papers we have counts for

collaborators

8 papers

cs.LG20224 cited

i-Code: An Integrative and Composable Multimodal Learning Framework

Ziyi Yang, Yuwei Fang, Chenguang Zhu +17

Human intelligence is multimodal; we integrate visual, linguistic, and acoustic signals to maintain a holistic worldview. Most current pretraining methods, however, are limited to…

cs.CL2021

A Simple and Effective Method To Eliminate the Self Language Bias in Multilingual Representations

Ziyi Yang, Yinfei Yang, Daniel Cer +1

Language agnostic and semantic-language information isolation is an emerging research direction for multilingual representations models. We explore this problem from a novel angle…

cs.CL2020

Universal Sentence Representation Learning with Conditional Masked Language Model

Ziyi Yang, Yinfei Yang, Daniel Cer +2

This paper presents a novel training method, Conditional Masked Language Modeling (CMLM), to effectively learn sentence representations on large scale unlabeled corpora. CMLM integ…

cs.LG20204 cited

Memory Augmented Generative Adversarial Networks for Anomaly Detection

Ziyi Yang, Teng Zhang, Iman Soltani Bozchalooi +1

In this paper, we present a memory-augmented algorithm for anomaly detection. Classical anomaly detection algorithms focus on learning to model and generate normal data, but typica…

cs.LG2020

Regularized Cycle Consistent Generative Adversarial Network for Anomaly Detection

Ziyi Yang, Iman Soltani Bozchalooi, Eric Darve

In this paper, we investigate algorithms for anomaly detection. Previous anomaly detection methods focus on modeling the distribution of non-anomalous data provided during training…

cs.CL2020

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising

Ziyi Yang, Chenguang Zhu, Robert Gmyr +3

Text summarization aims to extract essential information from a piece of text and transform the text into a concise version. Existing unsupervised abstractive summarization models…