no code implementations • 7 Feb 2022 • Seyyedali Hosseinalipour, Su Wang, Nicolo Michelusi, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Mung Chiang
PSL considers the realistic scenario where global aggregations are conducted with idle times in-between them for resource efficiency improvements, and incorporates data dispersion and model dispersion with local model condensation into FedL.
no code implementations • 25 Nov 2021 • Su Wang, Ceslee Montgomery, Jordi Orbay, Vighnesh Birodkar, Aleksandra Faust, Izzeddin Gur, Natasha Jaques, Austin Waters, Jason Baldridge, Peter Anderson
We study the automatic generation of navigation instructions from 360-degree images captured on indoor routes.
no code implementations • 8 Nov 2021 • Su Wang, Zhiliang Wang, Tao Zhou, Xia Yin, Dongqi Han, Han Zhang, Hongbin Sun, Xingang Shi, Jiahai Yang
Recent studies propose leveraging the rich contextual information in data provenance to detect threats in a host.
1 code implementation • 23 Sep 2021 • Dongqi Han, Zhiliang Wang, Wenqi Chen, Ying Zhong, Su Wang, Han Zhang, Jiahai Yang, Xingang Shi, Xia Yin
Experimental results show that DeepAID can provide high-quality interpretations for unsupervised DL models while meeting the special requirements of security domains.
no code implementations • 29 Jun 2021 • Su Wang, Seyyedali Hosseinalipour, Maria Gorlatova, Christopher G. Brinton, Mung Chiang
The presence of time-varying data heterogeneity and computational resource inadequacy among device clusters motivate four key parts of our methodology: (i) stratified UAV swarms of leader, worker, and coordinator UAVs, (ii) hierarchical nested personalized federated learning (HN-PFL), a distributed ML framework for personalized model training across the worker-leader-core network hierarchy, (iii) cooperative UAV resource pooling to address computational inadequacy of devices by conducting model training among the UAV swarms, and (iv) model/concept drift to model time-varying data distributions.
no code implementations • EACL 2021 • Ming Zhao, Peter Anderson, Vihan Jain, Su Wang, Alexander Ku, Jason Baldridge, Eugene Ie
Vision-and-Language Navigation wayfinding agents can be enhanced by exploiting automatically generated navigation instructions.
no code implementations • 4 Jan 2021 • Su Wang, Mengyuan Lee, Seyyedali Hosseinalipour, Roberto Morabito, Mung Chiang, Christopher G. Brinton
The conventional federated learning (FedL) architecture distributes machine learning (ML) across worker devices by having them train local models that are periodically aggregated by a server.
no code implementations • 1 Jan 2021 • Xiaolei Hua, Su Wang, Lin Zhu, Dong Zhou, Junlan Feng, Yiting Wang, Chao Deng, Shuo Wang, Mingtao Mei
However, due to complex correlations and various temporal patterns of large-scale multivariate time series, a general unsupervised anomaly detection model with higher F1-score and Timeliness remains a challenging task.
no code implementations • 17 Aug 2020 • Su Wang, Greg Durrett, Katrin Erk
We propose a method for controlled narrative/story generation where we are able to guide the model to produce coherent narratives with user-specified target endings by interpolation: for example, we are told that Jim went hiking and at the end Jim needed to be rescued, and we want the model to incrementally generate steps along the way.
no code implementations • 17 Apr 2020 • Yuwei Tu, Yichen Ruan, Su Wang, Satyavrat Wagle, Christopher G. Brinton, Carlee Joe-Wong
Unlike traditional federated learning frameworks, our method enables devices to offload their data processing tasks to each other, with these decisions determined through a convex data transfer optimization problem that trades off costs associated with devices processing, offloading, and discarding data points.
Distributed, Parallel, and Cluster Computing
no code implementations • IJCNLP 2019 • Su Wang, Greg Durrett, Katrin Erk
The news coverage of events often contains not one but multiple incompatible accounts of what happened.
no code implementations • EMNLP 2018 • Su Wang, Eric Holgate, Greg Durrett, Katrin Erk
During natural disasters and conflicts, information about what happened is often confusing, messy, and distributed across many sources.
no code implementations • 31 Oct 2018 • Su Wang, Rahul Gupta, Nancy Chang, Jason Baldridge
Paraphrasing is rooted in semantics.
1 code implementation • NAACL 2018 • Su Wang, Greg Durrett, Katrin Erk
Distributional data tells us that a man can swallow candy, but not that a man can swallow a paintball, since this is never attested.
1 code implementation • IJCNLP 2017 • Su Wang, Elisa Ferracane, Raymond J. Mooney
We explore techniques to maximize the effectiveness of discourse information in the task of authorship attribution.
no code implementations • IJCNLP 2017 • Su Wang, Stephen Roller, Katrin Erk
We test whether distributional models can do one-shot learning of definitional properties from text only.