1 code implementation • 28 Apr 2008 • Jian Ma, Zengqi Sun
In this paper, a theoretical framework for such estimation based on copula and copula entropy -- the probabilistic theory of representation and measurement of statistical dependence, is proposed.
no code implementations • 25 Jan 2016 • Jack P. Hou, Amin Emad, Gregory J. Puleo, Jian Ma, Olgica Milenkovic
To test $C^3$, we performed a detailed analysis on TCGA breast cancer and glioblastoma data and showed that our algorithm outperforms the state-of-the-art CoMEt method in terms of discovering mutually exclusive gene modules and identifying driver genes.
no code implementations • NeurIPS 2017 • Pan Xu, Jian Ma, Quanquan Gu
In order to speed up the estimation of the sparse plus low-rank components, we propose a sparsity constrained maximum likelihood estimator based on matrix factorization, and an efficient alternating gradient descent algorithm with hard thresholding to solve it.
1 code implementation • 29 Aug 2017 • Shashank Singh, Barnabás Póczos, Jian Ma
Sparse dictionary learning (SDL) has become a popular method for adaptively identifying parsimonious representations of a dataset, a fundamental problem in machine learning and signal processing.
no code implementations • NeurIPS 2017 • Pan Xu, Jian Ma, Quanquan Gu
In order to speed up the estimation of the sparse plus low-rank components, we propose a sparsity constrained maximum likelihood estimator based on matrix factorization and an efficient alternating gradient descent algorithm with hard thresholding to solve it.
2 code implementations • 31 May 2018 • Benjamin Chidester, Minh N. Do, Jian Ma
Performance of neural networks can be significantly improved by encoding known invariance for particular tasks.
no code implementations • ICML 2018 • Jinghui Chen, Pan Xu, Lingxiao Wang, Jian Ma, Quanquan Gu
We propose a nonconvex estimator for the covariate adjusted precision matrix estimation problem in the high dimensional regime, under sparsity constraints.
1 code implementation • 29 Jul 2019 • Jian Ma
Discovering associations is of central importance in scientific practices.
3 code implementations • 10 Oct 2019 • Jian Ma
Causal discovery is a fundamental problem in statistics and has wide applications in different fields.
1 code implementation • 28 Oct 2019 • Jian Ma
It is believed that CE based variable selection can help to build more explainable models.
1 code implementation • ICLR 2020 • Ruochi Zhang, Yuesong Zou, Jian Ma
Graph representation learning for hypergraphs can be used to extract patterns among higher-order interactions that are critically important in many real world problems.
no code implementations • 23 Feb 2020 • Jian Ma
As a byproduct, the associations between TUG score and several gait characteristics are discovered, which laid the scientific foundation of the proposed method and make the predictive models such built interpretable to clinical users.
no code implementations • 27 Feb 2020 • Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi
In this paper, we present a graph representation learning method atop of transaction networks for merchant incentive optimization in mobile payment marketing.
no code implementations • 18 Apr 2020 • Jian Ma
Based on measurement of finger tapping movement, the pipeline is first to select finger-tapping attributes with copula entropy and then to predict MMSE score from the selected attributes with predictive models.
no code implementations • 2020 Prognostics and Health Management Conference (PHM-Besançon) 2020 • Khaled Benaggoune, Safa Meraghni, Jian Ma, L.H MOUSS, Noureddine Zerhouni
This paper investigates the use of the Particle Swarm Optimization (PSO) algorithm to quantify the effect of RUL uncertainty on predictive maintenance planning.
1 code implementation • 27 May 2020 • Jian Ma
Copula Entropy is a mathematical concept defined by Ma and Sun for multivariate statistical independence measuring and testing, and also proved to be closely related to conditional independence (or transfer entropy).
7 code implementations • 23 Jun 2020 • Dima Damen, Hazel Doughty, Giovanni Maria Farinella, Antonino Furnari, Evangelos Kazakos, Jian Ma, Davide Moltisanti, Jonathan Munro, Toby Perrett, Will Price, Michael Wray
This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS.
Ranked #6 on Action Anticipation on EPIC-KITCHENS-100
no code implementations • 30 Jun 2020 • Jian Ma
To address the elderly's issues on dementia and fall risk, we have investigated smart cognitive and fall risk assessment with machine learning methodology based on the data collected from finger tapping test and Timed Up and Go (TUG) test.
no code implementations • SEMEVAL 2020 • Shuyi Xie, Jian Ma, Haiqin Yang, Jiang Lianxin, Mo Yang, Jianping Shen
The goal of this task is to extract definition, word level BIO tags and relations.
no code implementations • SEMEVAL 2020 • Jian Ma, Shuyi Xie, Meizhi Jin, Jiang Lianxin, Mo Yang, Jianping Shen
In this paper, we only report our implement of Subtask 2.
no code implementations • SEMEVAL 2021 • Shuyi Xie, Jian Ma, Haiqin Yang, Lianxin Jiang, Yang Mo, Jianping Shen
Second, we construct a new vector on the fine-tuned embeddings from XLM-RoBERTa and feed it to a fully-connected network to output the probability of whether the target word in the context has the same meaning or not.
no code implementations • SEMEVAL 2021 • Xiaoyi Ruan, Meizhi Jin, Jian Ma, Haiqin Yang, Lianxin Jiang, Yang Mo, Mengyuan Zhou
Question answering from semi-structured tables can be seen as a semantic parsing task and is significant and practical for pushing the boundary of natural language understanding.
no code implementations • SEMEVAL 2021 • Jian Ma, Shuyi Xie, Haiqin Yang, Lianxin Jiang, Mengyuan Zhou, Xiaoyi Ruan, Yang Mo
This paper describes MagicPai's system for SemEval 2021 Task 7, HaHackathon: Detecting and Rating Humor and Offense.
no code implementations • 7 Sep 2021 • Mengyuan Zhou, Jian Ma, Haiqin Yang, Lianxin Jiang, Yang Mo
In this paper, we target at how to further improve the token representations on the language models.
1 code implementation • 5 Nov 2021 • Yuhang Li, Mingzhu Shen, Jian Ma, Yan Ren, Mingxin Zhao, Qi Zhang, Ruihao Gong, Fengwei Yu, Junjie Yan
Surprisingly, no existing algorithm wins every challenge in MQBench, and we hope this work could inspire future research directions.
no code implementations • Studies in Autonomic, Data-driven and Industrial Computing 2022 • Khaled Benaggoune, Zeina Al Masry, Jian Ma, Christine Devalland, S. VALMARY-DEGANO, L.H MOUSS, Noureddine Zerhouni
The aim of this study is to highlight the impact of data labeling on deep learning models.
no code implementations • 13 Jan 2022 • Jian Ma, Dima Damen
This paper proposes an interaction reasoning network for modelling spatio-temporal relationships between hands and objects in video.
1 code implementation • 27 Feb 2022 • Jian Ma
In this sense, causal DA is transformed as a causal discovery problem that finds invariant representation across domains through the conditional independence between the state variables and observable state of the system given interventions.
no code implementations • 14 Mar 2022 • Khaled Benaggoune, Zeina Al Masry, Jian Ma, Christine Devalland, L. H Mouss, Noureddine Zerhouni
The extracted nuclei are then divided into overlapped and non-overlapped regions based on eight geometric and statistical features.
no code implementations • arXiv 2022 • Khaled Benaggoune, Zeina Al Masry, Jian Ma, Christine Devalland, L.H MOUSS, Noureddine Zerhouni
The Ki-67 proliferation index is an essential biomarker that helps pathologists to diagnose andselect appropriate treatments.
2 code implementations • 15 May 2022 • Jian Ma
For the CI measures, two simulated data with normal distribution and Gumbel copula, and one real data (the Beijing air data) were utilized to test the CI measures in prespecified linear or nonlinear setting and real scenario.
1 code implementation • 4 Sep 2022 • Jian Ma
Variable selection is an important problem in statistics and machine learning.
3 code implementations • 26 Sep 2022 • Ahmad Darkhalil, Dandan Shan, Bin Zhu, Jian Ma, Amlan Kar, Richard Higgins, Sanja Fidler, David Fouhey, Dima Damen
VISOR annotates videos from EPIC-KITCHENS, which comes with a new set of challenges not encountered in current video segmentation datasets.
1 code implementation • 15 Jan 2023 • Jian Ma
In this paper we propose to use the CE-based estimator of TE to identify time lag in dynamical systems.
3 code implementations • 31 Mar 2023 • Jian Ma, Mingjun Zhao, Chen Chen, Ruichen Wang, Di Niu, Haonan Lu, Xiaodong Lin
Recent breakthroughs in the field of language-guided image generation have yielded impressive achievements, enabling the creation of high-quality and diverse images based on user instructions. Although the synthesis performance is fascinating, one significant limitation of current image generation models is their insufficient ability to generate text coherently within images, particularly for complex glyph structures like Chinese characters.
Optical Character Recognition (OCR) Text-to-Image Generation
1 code implementation • 23 Apr 2023 • Jian Ma
In this paper we propose a method for identifying differential equation of dynamical systems with CE.
1 code implementation • 26 Apr 2023 • Muyu Yang, Jian Ma
The spatial positioning of chromosomes relative to functional nuclear bodies is intertwined with genome functions such as transcription.
1 code implementation • 27 Apr 2023 • Defeng Xie, Ruichen Wang, Jian Ma, Chen Chen, Haonan Lu, Dong Yang, Fobo Shi, Xiaodong Lin
We introduce a new generative system called Edit Everything, which can take image and text inputs and produce image outputs.
1 code implementation • 23 May 2023 • Ruichen Wang, Zekang Chen, Chen Chen, Jian Ma, Haonan Lu, Xiaodong Lin
Our approach produces a more semantically accurate synthesis by constraining the attention regions of each token in the prompt to the image.
1 code implementation • 21 Jul 2023 • Jian Ma, Junhao Liang, Chen Chen, Haonan Lu
In this paper, we propose Subject-Diffusion, a novel open-domain personalized image generation model that, in addition to not requiring test-time fine-tuning, also only requires a single reference image to support personalized generation of single- or multi-subject in any domain.
Diffusion Personalization Tuning Free Text-to-Image Generation
no code implementations • 15 Sep 2023 • Marinka Zitnik, Michelle M. Li, Aydin Wells, Kimberly Glass, Deisy Morselli Gysi, Arjun Krishnan, T. M. Murali, Predrag Radivojac, Sushmita Roy, Anaïs Baudot, Serdar Bozdag, Danny Z. Chen, Lenore Cowen, Kapil Devkota, Anthony Gitter, Sara Gosline, Pengfei Gu, Pietro H. Guzzi, Heng Huang, Meng Jiang, Ziynet Nesibe Kesimoglu, Mehmet Koyuturk, Jian Ma, Alexander R. Pico, Nataša Pržulj, Teresa M. Przytycka, Benjamin J. Raphael, Anna Ritz, Roded Sharan, Yang shen, Mona Singh, Donna K. Slonim, Hanghang Tong, Xinan Holly Yang, Byung-Jun Yoon, Haiyuan Yu, Tijana Milenković
As such, it is expected to help shape short- and long-term vision for future computational and algorithmic research in network biology.
1 code implementation • 25 Oct 2023 • Jian Ma
In this paper we propose to apply copula entropy (CE) to photometric redshifts.
1 code implementation • 28 Nov 2023 • Jian Ma, Chen Chen, Qingsong Xie, Haonan Lu
In this paper, we are inspired to propose a simple plug-and-play language transfer method based on knowledge distillation.
Cross-lingual Text-to-Image Generation Knowledge Distillation +1
no code implementations • 4 Dec 2023 • Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong
To help merchants/customers to provide/access a variety of services through miniapps, online service platforms have occupied a critical position in the effective content delivery, in which how to recommend items in the new domain launched by the service provider for customers has become more urgent.
no code implementations • 10 Dec 2023 • Yi Wang, Jian Ma, Ruizhi Shao, Qiao Feng, Yu-Kun Lai, Yebin Liu, Kun Li
To keep the generated clothing consistent with the target text, we propose a semantic-confidence strategy for clothing that can eliminate the non-clothing content generated by the model.
1 code implementation • 15 Dec 2023 • Yuhang Ming, Jian Ma, Xingrui Yang, Weichen Dai, Yong Peng, Wanzeng Kong
We evaluate our AEGIS-Net on the ScanNetPR dataset and compare its performance with a pre-deep-learning feature-based method and five state-of-the-art deep-learning-based methods.
1 code implementation • 11 Jan 2024 • Yue Liu, Shihao Zhu, Jun Xia, Yingwei Ma, Jian Ma, Wenliang Zhong, Xinwang Liu, Guannan Zhang, Kejun Zhang
Concretely, we encode users' behavior sequences and initialize the cluster centers (latent intents) as learnable neurons.
no code implementations • 11 Jan 2024 • Jian Ma
A method, called TE flow, is proposed in that a TE flow from physical measurements of each subsystem to the energy efficiency indicator along timeline is considered as causal strength for diagnosing root cause of anomaly states of energy efficiency of a system.
no code implementations • 19 Jan 2024 • Hao Ai, Zidong Cao, Haonan Lu, Chen Chen, Jian Ma, Pengyuan Zhou, Tae-Kyun Kim, Pan Hui, Lin Wang
To this end, we propose a transformer-based 360 image outpainting framework called Dream360, which can generate diverse, high-fidelity, and high-resolution panoramas from user-selected viewports, considering the spherical properties of 360 images.
no code implementations • 23 Jan 2024 • Nikki Bialy, Frank Alber, Brenda Andrews, Michael Angelo, Brian Beliveau, Lacramioara Bintu, Alistair Boettiger, Ulrike Boehm, Claire M. Brown, Mahmoud Bukar Maina, James J. Chambers, Beth A. Cimini, Kevin Eliceiri, Rachel Errington, Orestis Faklaris, Nathalie Gaudreault, Ronald N. Germain, Wojtek Goscinski, David Grunwald, Michael Halter, Dorit Hanein, John W. Hickey, Judith Lacoste, Alex Laude, Emma Lundberg, Jian Ma, Leonel Malacrida, Josh Moore, Glyn Nelson, Elizabeth Kathleen Neumann, Roland Nitschke, Shuichi Onami, Jaime A. Pimentel, Anne L. Plant, Andrea J. Radtke, Bikash Sabata, Denis Schapiro, Johannes Schöneberg, Jeffrey M. Spraggins, Damir Sudar, Wouter-Michiel Adrien Maria Vierdag, Niels Volkmann, Carolina Wählby, Siyuan, Wang, Ziv Yaniv, Caterina Strambio-De-Castillia
Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health.
2 code implementations • 3 Feb 2024 • Jian Ma
In this paper we propose a nonparametric multivariate method for multiple change point detection with the copula entropy-based two-sample test.