Shuiwang Ji

According to our database1, Shuiwang Ji
  • authored at least 73 papers between 2007 and 2017.
  • has a "Dijkstra number"2 of three.

Timeline

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Bibliography

2017
Feature Selection Based on Structured Sparsity: A Comprehensive Study.
IEEE Trans. Neural Netw. Learning Syst., 2017

Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction.
IEEE Trans. Med. Imaging, 2017

Residual Deconvolutional Networks for Brain Electron Microscopy Image Segmentation.
IEEE Trans. Med. Imaging, 2017

Efficient and Invariant Convolutional Neural Networks for Dense Prediction.
CoRR, 2017

Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions.
CoRR, 2017

Learning Convolutional Text Representations for Visual Question Answering.
CoRR, 2017

Dense Transformer Networks.
CoRR, 2017

Pixel Deconvolutional Networks.
CoRR, 2017

Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation.
CoRR, 2017

DeepEM3D: approaching human-level performance on 3D anisotropic EM image segmentation.
Bioinformatics, 2017

Multi-Modality Disease Modeling via Collective Deep Matrix Factorization.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

IDM 2017: Workshop on Interpretable Data Mining - Bridging the Gap between Shallow and Deep Models.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016
Deep models for brain EM image segmentation: novel insights and improved performance.
Bioinformatics, 2016

Collaborative Multi-View Denoising.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Multi-Task Feature Interaction Learning.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Parallel Lasso Screening for Big Data Optimization.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Deep convolutional neural networks for detecting secondary structures in protein density maps from cryo-electron microscopy.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015
Sparsity Learning Formulations for Mining Time-Varying Data.
IEEE Trans. Knowl. Data Eng., 2015

A Robust Deep Model for Improved Classification of AD/MCI Patients.
IEEE J. Biomedical and Health Informatics, 2015

Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.
NeuroImage, 2015

Evolutionary soft co-clustering: formulations, algorithms, and applications.
Data Min. Knowl. Discov., 2015

Global analysis of gene expression and projection target correlations in the mouse brain.
Brain Informatics, 2015

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.
BMC Bioinformatics, 2015

Automated Gene Expression Pattern Annotation in the Mouse Brain.
Proceedings of the Biocomputing 2015: Proceedings of the Pacific Symposium, 2015

Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Structural Graphical Lasso for Learning Mouse Brain Connectivity.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Deep Convolutional Neural Networks for Multi-instance Multi-task Learning.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

2014
How to Estimate the Regularization Parameter for Spectral Regression Discriminant Analysis and its Kernel Version?
IEEE Trans. Circuits Syst. Video Techn., 2014

Integrative analysis of the connectivity and gene expression atlases in the mouse brain.
NeuroImage, 2014

Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns.
BMC Bioinformatics, 2014

Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression.
Bioinformatics, 2014

Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

Robust Deep Learning for Improved Classification of AD/MCI Patients.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014

2013
Multiview Partitioning via Tensor Methods.
IEEE Trans. Knowl. Data Eng., 2013

A Probabilistic Latent Semantic Analysis Model for Coclustering the Mouse Brain Atlas.
IEEE/ACM Trans. Comput. Biology Bioinform., 2013

3D Convolutional Neural Networks for Human Action Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis.
BMC Bioinformatics, 2013

Image-level and group-level models for Drosophila gene expression pattern annotation.
BMC Bioinformatics, 2013

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.
BMC Bioinformatics, 2013

Evolutionary Soft Co-Clustering.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

2012
Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning.
IEEE/ACM Trans. Comput. Biology Bioinform., 2012

Discriminant sparse neighborhood preserving embedding for face recognition.
Pattern Recognition, 2012

Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization
CoRR, 2012

Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval.
BMC Bioinformatics, 2012

A sparsity-inducing formulation for evolutionary co-clustering.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

2011
Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2011

FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis.
Bioinformatics, 2011

Computational network analysis of the anatomical and genetic organizations in the mouse brain.
Bioinformatics, 2011

2010
A shared-subspace learning framework for multi-label classification.
TKDD, 2010

Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning.
SIAM Journal on Optimization, 2010

3D Convolutional Neural Networks for Human Action Recognition.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009
A bag-of-words approach for Drosophila gene expression pattern annotation.
BMC Bioinformatics, 2009

Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization.
Proceedings of the UAI 2009, 2009

Mining discrete patterns via binary matrix factorization.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Drosophila gene expression pattern annotation using sparse features and term-term interactions.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares.
Proceedings of the IJCAI 2009, 2009

DrosophilaGene Expression Pattern Annotation through Multi-Instance Multi-Label Learning.
Proceedings of the IJCAI 2009, 2009

Linear Dimensionality Reduction for Multi-label Classification.
Proceedings of the IJCAI 2009, 2009

A least squares formulation for a class of generalized eigenvalue problems in machine learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

An accelerated gradient method for trace norm minimization.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection.
IEEE Trans. Neural Networks, 2008

Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational Study.
IEEE Trans. Knowl. Data Eng., 2008

Multi-class Discriminant Kernel Learning via Convex Programming.
Journal of Machine Learning Research, 2008

Adaptive diffusion kernel learning from biological networks for protein function prediction.
BMC Bioinformatics, 2008

Automated annotation of Drosophila gene expression patterns using a controlled vocabulary.
Bioinformatics, 2008

Multi-label Multiple Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Hypergraph spectral learning for multi-label classification.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Extracting shared subspace for multi-label classification.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Learning subspace kernels for classification.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

A least squares formulation for canonical correlation analysis.
Proceedings of the Machine Learning, 2008

A unified framework for generalized Linear Discriminant Analysis.
Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Discriminant kernel and regularization parameter learning via semidefinite programming.
Proceedings of the Machine Learning, 2007


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