no code implementations • EMNLP (sustainlp) 2021 • Zachary Zhou, Jeffery Kline, Devin Conathan, Glenn Fung
We address the problem of link prediction between entities and relations of knowledge graphs.
1 code implementation • 18 Nov 2021 • Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh
In this paper, we show that a Bernoulli sampling attention mechanism based on Locality Sensitive Hashing (LSH), decreases the quadratic complexity of such models to linear.
no code implementations • 29 Oct 2021 • Jaya Krishna Mandivarapu, Eric Bunch, Glenn Fung
In this work, we address the problem of few-shot document image classification under domain shift.
1 code implementation • Proceedings of the VLDB Endowment 2021 • Saravanan Thirumuruganathan, Han Li, Nan Tang, Mourad Ouzzani, Yash Govind, Derek Paulsen, Glenn Fung, AnHai Doan
In this paper, we develop the DeepBlocker framework that significantly advances the state of the art in applying DL to blocking for EM.
Ranked #5 on Blocking on Abt-Buy
no code implementations • 25 Jun 2021 • Jaya Krishna Mandivarapu, Eric Bunch, Qian You, Glenn Fung
Recent advancements in large pre-trained computer vision and language models and graph neural networks has lent document image classification many tools.
Ranked #1 on Document Image Classification on Tobacco-3482 (Memory metric)
no code implementations • NeurIPS Workshop TDA_and_Beyond 2020 • Eric Bunch, Jeffery Kline, Daniel Dickinson, Suhaas Bhat, Glenn Fung
Metric space magnitude, an active field of research in algebraic topology, is a scalar quantity that summarizes the effective number of distinct points that live in a general metric space.
6 code implementations • 7 Feb 2021 • Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh
The scalability of Nystr\"{o}mformer enables application to longer sequences with thousands of tokens.
Ranked #13 on Semantic Textual Similarity on MRPC (F1 metric)
no code implementations • 31 Jan 2021 • Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh Kim, Glenn Fung
Customer satisfaction is an important factor in creating and maintaining long-term relationships with customers.
1 code implementation • 31 Jan 2021 • Teja Kanchinadam, Qian You, Keith Westpfahl, James Kim, Siva Gunda, Sebastian Seith, Glenn Fung
In this work, we propose the use of a fully managed machine learning service, which utilizes active learning to directly build models from unstructured data.
no code implementations • 30 Dec 2020 • Victor Luo, Yazhen Wang, Glenn Fung
In this paper, we seek to extend the mean field results of Mei et al. (2018) from two-layer neural networks with one hidden layer to three-layer neural networks with two hidden layers.
no code implementations • NeurIPS Workshop TDA_and_Beyond 2020 • Eric Bunch, Qian You, Glenn Fung, Vikas Singh
Recently, neural network architectures have been developed to accommodate when the data has the structure of a graph or, more generally, a hypergraph.
no code implementations • 24 Jun 2020 • Eric Bunch, Daniel Dickinson, Jeffery Kline, Glenn Fung
In a more general setting, the magnitude of a metric space is a real number that aims to quantify the effective number of distinct points in the space.
no code implementations • 8 Nov 2018 • Luisa Polania, Dongning Wang, Glenn Fung
Ordinal regression aims to classify instances into ordinal categories.
1 code implementation • ECCV 2018 • Zihang Meng, Nagesh Adluru, Hyunwoo J. Kim, Glenn Fung, Vikas Singh
A sizable body of work on relative attributes provides compelling evidence that relating pairs of images along a continuum of strength pertaining to a visual attribute yields significant improvements in a wide variety of tasks in vision.
no code implementations • 30 May 2016 • Ramanathan Subramanian, Romer Rosales, Glenn Fung, Jennifer Dy
Given a supervised/semi-supervised learning scenario where multiple annotators are available, we consider the problem of identification of adversarial or unreliable annotators.