Kai Zhang

According to our database1, Kai Zhang authored at least 47 papers between 2005 and 2018.

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Bibliography

2018
Neural and genetic determinants of creativity.
NeuroImage, 2018

Network Inference from Contrastive Groups Using Discriminative Structural Regularization.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

DisTenC: A Distributed Algorithm for Scalable Tensor Completion on Spark.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Collaborative Alert Ranking for Anomaly Detection.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamical Analysis on Vanishing Correlations.
TKDD, 2017

Low-rank decomposition meets kernel learning: A generalized Nyström method.
Artif. Intell., 2017

Randomization or Condensation?: Linear-Cost Matrix Sketching Via Cascaded Compression Sampling.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Efficient Discovery of Abnormal Event Sequences in Enterprise Security Systems.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016
Temporal Skeletonization on Sequential Data: Patterns, Categorization, and Visualization.
IEEE Trans. Knowl. Data Eng., 2016

Enhancing semi-supervised learning through label-aware base kernels.
Neurocomputing, 2016

Seeing the Forest from the Trees in Two Looks: Matrix Sketching by Cascaded Bilateral Sampling.
CoRR, 2016

GID: Graph-based Intrusion Detection on Massive Process Traces for Enterprise Security Systems.
CoRR, 2016

Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events.
CoRR, 2016

Distributed Flexible Nonlinear Tensor Factorization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Annealed Sparsity via Adaptive and Dynamic Shrinking.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Entity Embedding-Based Anomaly Detection for Heterogeneous Categorical Events.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines.
IEEE Trans. Neural Netw. Learning Syst., 2015

From Categorical to Numerical: Multiple Transitive Distance Learning and Embedding.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Efficient Long-Term Degradation Profiling in Time Series for Complex Physical Systems.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

A Quality Control Engine for Complex Physical Systems.
Proceedings of the 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2015

2014
Sparse semi-supervised learning on low-rank kernel.
Neurocomputing, 2014

Temporal skeletonization on sequential data: patterns, categorization, and visualization.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Sequential Pattern Analysis with Right Granularity.
Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014

Improving Semi-Supervised Target Alignment via Label-Aware Base Kernels.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method
CoRR, 2012

Patient-friendly detection of early peripheral arterial diseases (PAD) by budgeted sensor selection.
Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare, 2012

Improved Nystrom Low-rank Decomposition with Priors.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Comparison of sparse coding and kernel methods for histopathological classification of gliobastoma multiforme.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

2010
Clustered Nyström method for large scale manifold learning and dimension reduction.
IEEE Trans. Neural Networks, 2010

Simplifying mixture models through function approximation.
IEEE Trans. Neural Networks, 2010

Rhythmic Dynamics and Synchronization via Dimensionality Reduction: Application to Human Gait.
PLoS Computational Biology, 2010

Fast and accurate kernel density approximation using a divide-and-conquer approach.
Journal of Zhejiang University - Science C, 2010

Sparse multitask regression for identifying common mechanism of response to therapeutic targets.
Bioinformatics [ISMB], 2010

2009
Maximum Margin Clustering Made Practical.
IEEE Trans. Neural Networks, 2009

Density-Weighted Nyström Method for Computing Large Kernel Eigensystems.
Neural Computation, 2009

Prototype vector machine for large scale semi-supervised learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Improved Nyström low-rank approximation and error analysis.
Proceedings of the Machine Learning, 2008

2007
Maximum margin clustering made practical.
Proceedings of the Machine Learning, 2007

2006
Chaos inducement and Enhancement in Two Particular Nonlinear Maps Using Weak Periodic/quasiperiodic Perturbations.
I. J. Bifurcation and Chaos, 2006

Simplifying Mixture Models through Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Block-quantized kernel matrix for fast spectral embedding.
Proceedings of the Machine Learning, 2006

Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Accelerated Convergence Using Dynamic Mean Shift.
Proceedings of the Computer Vision, 2006

2005
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005


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