Publications

  • How Does Noise Help Robustness? Stabilizing Neural ODE Networks with Stochastic Noise
    In CVPR 2020(Oral)
  • A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
    In NeurIPS 2019
  • Robustness Verification of Tree-based Models
    In NeurIPS 2019
  • Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
    In KDD 2019 (Oral)
  • Area Attention
    In ICML 2019
  • GaterNet: Dynamic Filter Selection in Convolutional Neural Network via a Dedicated Global Gating Network
    In CVPR 2019
  • Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Network
    In ICLR 2019
  • GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
    In NIPS 2018
  • GPU-acceleration for Large-scale Tree Boosting
    In SysML 2018
  • Nonlinear Online Learning with Adaptive Nystrom Approximation
    In arXiv:1802.07887
  • Gradient Boosted Decision Trees for High Dimensional Sparse Output
    In ICML 2017
  • Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines
    In KDD 2017 (Oral)
  • Memory efficient kernel approximation
    JMLR 2017
  • Goal-directed inductive matrix completion
    In KDD 2016 (Oral)
  • Computationally Efficient Nystrom Approximation using Fast Transforms
    In ICML 2016
  • Kernel Ridge Regression via Partitioning
    In arXiv:1608.01976
  • Fast prediction for large-scale kernel machines
    In NIPS 2014
  • Multi-scale spectral decomposition of massive graphs
    In NIPS 2014
  • Parallel matrix factorization for recommender systems
    Knowledge and Information Systems 2014
  • A Divide-and-Conquer Solver for Kernel Support Vector Machines
    In ICML 2014
  • Memory Ef´Čücient Kernel Approximation
    In ICML 2014
  • Beyond modeling private actions: predicting social shares
    In WWW 2014 (short paper)
  • The expression gap: do you like what you share?
    In WWW 2014 (short paper)
  • Multi-scale link prediction
    In CIKM 2012
  • Scalable coordinate descent approaches to parallel matrix factorization for recommender systems
    In ICDM 2012 (best paper)
  • Distribution calibration in Riemannian symmetric space
    IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 2011
  • Evolutionary cross-domain discriminative Hessian eigenmaps
    IEEE Transactions on Image Processing 2010
  • Bregman divergence-based regularization for transfer subspace learning
    IEEE Transactions on Knowledge and Data Engineering 2010
  • Discriminative Hessian Eigenmaps for face recognition
    In ICASSP 2010

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Contact

  • contact (at) sisihku@gmail (dot) com