Search Results for author: Jian Ma

Found 24 papers, 8 papers with code

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

1 code implementation5 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.

Quantization

Sequential Attention Module for Natural Language Processing

no code implementations7 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.

Fine-tuning Language Modelling +1

Sattiy at SemEval-2021 Task 9: An Ensemble Solution for Statement Verification and Evidence Finding with Tables

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.

Language understanding Natural Language Understanding +2

PALI at SemEval-2021 Task 2: Fine-Tune XLM-RoBERTa for Word in Context Disambiguation

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.

Data Augmentation

Associations between finger tapping, gait and fall risk with application to fall risk assessment

no code implementations30 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.

copent: Estimating Copula Entropy and Transfer Entropy in R

1 code implementation27 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).

Causal Discovery Mutual Information Estimation +2

Predicting MMSE Score from Finger-Tapping Measurement

no code implementations18 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.

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing

no code implementations27 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.

Graph Representation Learning

Predicting TUG score from gait characteristics with video analysis and machine learning

no code implementations23 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.

Hyper-SAGNN: a self-attention based graph neural network for hypergraphs

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.

Graph Representation Learning

Variable Selection with Copula Entropy

1 code implementation28 Oct 2019 Jian Ma

It is believed that CE based variable selection can help to build more explainable models.

Feature Importance Feature Selection +1

Estimating Transfer Entropy via Copula Entropy

2 code implementations10 Oct 2019 Jian Ma

Causal discovery is a fundamental problem in statistics and has wide applications in different fields.

Causal Discovery Causal Inference

Discovering Association with Copula Entropy

no code implementations29 Jul 2019 Jian Ma

Discovering associations is of central importance in scientific practices.

Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization

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.

Rotation Equivariance and Invariance in Convolutional Neural Networks

2 code implementations31 May 2018 Benjamin Chidester, Minh N. Do, Jian Ma

Performance of neural networks can be significantly improved by encoding known invariance for particular tasks.

Classification General Classification +1

Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization

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.

On the Reconstruction Risk of Convolutional Sparse Dictionary Learning

1 code implementation29 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.

Dictionary Learning Time Series

Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimizations

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.

A new correlation clustering method for cancer mutation analysis

no code implementations25 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.

Community Detection

Dependence Structure Estimation via Copula

no code implementations28 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.

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