Kai Zhang

Orcid: 0000-0001-6297-4423

Affiliations:
  • Temple University, Department of Computer and Information Sciences, Philadelphia, PA, USA (since 2017)
  • NEC Labs. America, Princeton, NJ, USA (2013 - 2017)
  • Siemens Corporate Rearch (2010 - 2013)
  • Lawrence Berkeley National Lab, CA, USA (2008 - 2010)
  • Hong Kong University of Science and Technology (PhD 2008)


According to our database1, Kai Zhang authored at least 71 papers between 2005 and 2024.

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Bibliography

2024
A Transformative Topological Representation for Link Modeling, Prediction and Cross-Domain Network Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2024

Building Shortcuts between Distant Nodes with Biaffine Mapping for Graph Convolutional Networks.
ACM Trans. Knowl. Discov. Data, July, 2024

DPGCL: Dual pass filtering based graph contrastive learning.
Neural Networks, 2024

Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation.
CoRR, 2024

Knowledge Graph Information Bottleneck for Drug-Drug Interaction Prediction.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
Fast Convolutional Factorization Machine With Enhanced Robustness.
IEEE Trans. Knowl. Data Eng., March, 2023

Diagnostic Sparse Connectivity Networks With Regularization Template.
IEEE Trans. Knowl. Data Eng., 2023

2022
Node Embedding and Classification with Adaptive Structural Fingerprint.
Neurocomputing, 2022

APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction.
CoRR, 2022

Multi-modal chemical information reconstruction from images and texts for exploring the near-drug space.
Briefings Bioinform., 2022

APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Semantic consistency for graph representation learning.
Proceedings of the International Joint Conference on Neural Networks, 2022

Structural Landmarking and Interaction Modelling: A "SLIM" Network for Graph Classification.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Anomalous Event Sequence Detection.
IEEE Intell. Syst., 2021

BEAUTY Powered BEAST.
CoRR, 2021

GMOT-40: A Benchmark for Generic Multiple Object Tracking.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Structural Landmarking and Interaction Modelling: on Resolution Dilemmas in Graph Classification.
CoRR, 2020

Adaptive Structural Fingerprints for Graph Attention Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Probabilistic Neural-Kernel Tensor Decomposition.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Online Bayesian Sparse Learning with Spike and Slab Priors.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach.
IEEE Trans. Neural Networks Learn. Syst., 2019

A Feature Sampling Strategy for Analysis of High Dimensional Genomic Data.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019

Augmented label propagation for seed set expansion.
Knowl. Based Syst., 2019

Brain annotation toolbox: exploring the functional and genetic associations of neuroimaging results.
Bioinform., 2019

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

NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & 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.
ACM Trans. Knowl. Discov. Data, 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

Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems.
Proceedings of the 2017 IEEE International Conference on Data Mining, 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

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 Networks Learn. 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 Comput. Biol., 2010

Fast and accurate kernel density approximation using a divide-and-conquer approach.
J. Zhejiang Univ. Sci. C, 2010

Sparse multitask regression for identifying common mechanism of response to therapeutic targets.
Bioinform., 2010

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

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

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