no code implementations • 20 Apr 2023 • Chao Cheng, Fan Li
In this article, we consider a semiparametric framework for assessing causal mediation in the presence of treatment noncompliance without the exclusion restriction.
no code implementations • 23 Feb 2023 • Dongdong Zou, Wei Wang, Sui Qi, Fan Li, Zhaohui Li
For the IM-DD system under peak power constraint (PPC), a dynamic-assignment BA algorithm is applied to find the capacity-achieving distribution with minimum cardinality.
no code implementations • 17 Feb 2023 • Hengyu Liu, Tiancheng Zhang, Fan Li, Minghe Yu, Ge Yu
To better model students' exercise responses, we proposed a logarithmic linear model with three interactive strategies, which models students' exercise responses by considering the relationship among students' knowledge status, knowledge concept, and problems.
no code implementations • 30 Nov 2022 • Fan Li, Bo wang, Pin Wang, Yongming Li
Secondly, according to the characteristics of subset classes, a stage-wise hybrid sampling algorithm is designed to realize the de-overlapping and balancing of subsets.
1 code implementation • 16 Nov 2022 • Fan Li, Hang Zhou, Huafeng Li, Yafei Zhang, Zhengtao Yu
Specifically, we improve the interpretability of text features by providing them with consistent semantic information with image features to achieve the alignment of text and describe image region features. To address the challenges posed by the diversity of text and the corresponding person images, we treat the variation caused by diversity to features as caused by perturbation information and propose a novel adversarial attack and defense method to solve it.
no code implementations • 25 Oct 2022 • Chuanyan Zhou, Jie Ma, Fan Li, Yongming Li, Pin Wang, Xiaoheng Zhang
Second, an embedded stack autoencoder (ESAE) is proposed and trained in each layer of sample space to consider the original samples during training and in the network structure, thereby better finding the relationship between original feature samples and deep feature samples.
no code implementations • 25 Jun 2022 • Fan Li, Xiaoheng Zhang, Yongming Li, Pin Wang
Based on the analysis above, an imbalanced ensemble algorithm with the deep sample pre-envelope network (DSEN) and local-global structure consistency mechanism (LGSCM) is proposed here to solve the problem. This algorithm can guarantee high-quality deep envelope samples for considering the local manifold and global structures information, which is helpful for imbalance learning.
no code implementations • 31 Mar 2022 • Cheng Dai, Yingqiao Lin, Fan Li, Xiyao Li, Donglin Xie
In Domain Generalization (DG) tasks, models are trained by using only training data from the source domains to achieve generalization on an unseen target domain, this will suffer from the distribution shift problem.
Ranked #3 on Domain Generalization on VLCS
no code implementations • 17 Nov 2021 • Yiwen Wang, Fan Li, Xiaoheng Zhang, Pin Wang, Yongming Li
Therefore, it is necessary to reconstruct the existing large segments within one subject into few segments even one segment within one subject, which can facilitate the extraction of relevant speech features to characterize diagnostic markers for the whole subject.
no code implementations • 2 Nov 2021 • Fan Li, Xiaoheng Zhang, Pin Wang, Yongming Li
However, all existing clustering methods are based on a one-time approach.
no code implementations • 9 Jul 2021 • Serge Assaad, Shuxi Zeng, Henry Pfister, Fan Li, Lawrence Carin
We examine interval estimation of the effect of a treatment T on an outcome Y given the existence of an unobserved confounder U.
1 code implementation • 2 Jul 2021 • Junya Chen, Zhe Gan, Xuan Li, Qing Guo, Liqun Chen, Shuyang Gao, Tagyoung Chung, Yi Xu, Belinda Zeng, Wenlian Lu, Fan Li, Lawrence Carin, Chenyang Tao
InfoNCE-based contrastive representation learners, such as SimCLR, have been tremendously successful in recent years.
1 code implementation • 2 Jul 2021 • Qing Guo, Junya Chen, Dong Wang, Yuewei Yang, Xinwei Deng, Lawrence Carin, Fan Li, Jing Huang, Chenyang Tao
Successful applications of InfoNCE and its variants have popularized the use of contrastive variational mutual information (MI) estimators in machine learning.
1 code implementation • 30 May 2021 • Jian Cui, Zirui Lan, Yisi Liu, Ruilin Li, Fan Li, Olga Sourina, Wolfgang Mueller-Wittig
Driver drowsiness is one of main factors leading to road fatalities and hazards in the transportation industry.
1 code implementation • 14 Mar 2021 • Zhenhua Wang, Olanrewaju Akande, Jason Poulos, Fan Li
We conduct extensive simulation studies based on a subsample of the American Community Survey to compare the repeated sampling properties of four machine learning based MI methods: MICE with classification trees, MICE with random forests, generative adversarial imputation networks, and multiple imputation using denoising autoencoders.
no code implementations • 11 Mar 2021 • Fan Li, Yongming Li, Pin Wang, Jie Xiao, Fang Yan, Xinke Li
Traditional age estimation mechanism focuses estimation age error, but ignores that there is a deviation between the estimated age and real age due to disease.
no code implementations • 8 Mar 2021 • Fan Li, Ashley L. Buchanan, Stephen R. Cole
Motivated by the need to generalize evidence from two trials conducted in the AIDS Clinical Trials Group (ACTG), we consider weighting, regression and doubly robust estimators to estimate the causal effects of HIV interventions in a specified population of people living with HIV in the USA.
no code implementations • 5 Jan 2021 • Tantan Zhao, Lijun He, Xinyu Huang, Fan Li
In this paper, by considering the interaction between video encoding and edge caching, we investigate the quality of experience (QoE)-driven cross-layer optimization of secure video transmission over the wireless backhaul link in cloud-edge collaborative networks.
1 code implementation • NeurIPS 2020 • Danni Lu, Chenyang Tao, Junya Chen, Fan Li, Feng Guo, Lawrence Carin
As a step towards more flexible, scalable and accurate ITE estimation, we present a novel generative Bayesian estimation framework that integrates representation learning, adversarial matching and causal estimation.
2 code implementations • 10 Nov 2020 • Yichao Cao, Qingfei Tang, Xiaobo Lu, Fan Li, Jinde Cao
To overcome these problems, a novel Spatio-Temporal Cross Network (STCNet) is proposed to recognize industrial smoke emissions.
no code implementations • 23 Oct 2020 • Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin
A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type.
no code implementations • 16 Oct 2020 • Xinyu Huang, Lijun He, Xing Chen, Liejun Wang, Fan Li
In this paper, we propose a joint task type and vehicle speed-aware task offloading and resource allocation strategy to decrease the vehicl's energy cost for executing tasks and increase the revenue of the vehicle for processing tasks within the delay constraint.
1 code implementation • 15 Oct 2020 • Shuxi Zeng, Serge Assaad, Chenyang Tao, Shounak Datta, Lawrence Carin, Fan Li
Causal inference, or counterfactual prediction, is central to decision making in healthcare, policy and social sciences.
1 code implementation • 17 Aug 2020 • Liangyuan Hu, Jiayi Ji, Fan Li
Methods for estimating heterogeneous treatment effect in observational data have largely focused on continuous or binary outcomes, and have been relatively less vetted with survival outcomes.
no code implementations • 9 Aug 2020 • Changhong Fu, Xiaoxiao Yang, Fan Li, Juntao Xu, Changjing Liu, Peng Lu
By minimizing the difference between the practical and the scheduled ideal consistency map, the consistency level is constrained to maintain temporal smoothness, and rich temporal information contained in response maps is introduced.
no code implementations • 20 Jun 2020 • Yongming Li, Lang Zhou, Lingyun Qin, Yuwei Zeng, Yuchuan Liu, Yan Lei, Pin Wang, Fan Li
To solve these two problems, based on the existing Parkinson speech feature data set, a deep double-side learning ensemble model is designed in this paper that can reconstruct speech features and samples deeply and simultaneously.
no code implementations • 10 Jun 2020 • Gary White, Christian Cabrera, Andrei Palade, Fan Li, Siobhan Clarke
In this paper, we propose WasteNet, a waste classification model based on convolutional neural networks that can be deployed on a low power device at the edge of the network, such as a Jetson Nano.
1 code implementation • 11 Mar 2020 • Fan Li, Changhong Fu, Fuling Lin, Yiming Li, Peng Lu
After the establishment of a new slot, the weighted fusion of the previous samples generates one key-sample, in order to reduce the number of samples to be scored.
no code implementations • 10 Sep 2019 • Haidong Rong, Yangzihao Wang, Feihu Zhou, Junjie Zhai, Haiyang Wu, Rui Lan, Fan Li, Han Zhang, Yuekui Yang, Zhenyu Guo, Di Wang
We present Distributed Equivalent Substitution (DES) training, a novel distributed training framework for large-scale recommender systems with dynamic sparse features.
6 code implementations • 13 Jan 2019 • Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivantik, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yu, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern Menze
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018.