Ke Sun

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 42

Top Topics

Minimum Description Length

Fisher Information

Laplacian Eigenmaps

Top Venues

IACR Cryptol. ePrint Arch.

Publications

Alexander Soen, Ke Sun
Tradeoffs of Diagonal Fisher Information Matrix Estimators. CoRR (2024)
Frank Nielsen, Ke Sun
Non-linear Embeddings in Hilbert Simplex Geometry. TAG-ML (2023)
Marcel Keller, Ke Sun
A Note on "Secure Quantized Training for Deep Learning". IACR Cryptol. ePrint Arch. 2023 (2023)
Alexander Soen, Ibrahim M. Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie
Fair Wrapping for Black-box Predictions. NeurIPS (2022)
Marcel Keller, Ke Sun
Secure Quantized Training for Deep Learning. ICML (2022)
Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie
Fair Wrapping for Black-box Predictions. CoRR (2022)
Frank Nielsen, Ke Sun
Non-linear Embeddings in Hilbert Simplex Geometry. CoRR (2022)
Marcel Keller, Ke Sun
Secure Quantized Training for Deep Learning. IACR Cryptol. ePrint Arch. 2022 (2022)
Hao Zhu, Ke Sun, Piotr Koniusz
Contrastive Laplacian Eigenmaps. CoRR (2022)
Alexander Soen, Ke Sun
On the Variance of the Fisher Information for Deep Learning. CoRR (2021)
Frank Nielsen, Ke Sun
q-Neurons: Neuron Activations Based on Stochastic Jackson's Derivative Operators. IEEE Trans. Neural Networks Learn. Syst. 32 (6) (2021)
Marcel Keller, Ke Sun
Secure Quantized Training for Deep Learning. CoRR (2021)
Hao Zhu, Ke Sun, Peter Koniusz
Contrastive Laplacian Eigenmaps. NeurIPS (2021)
Piotr Koniusz, Lei Wang, Ke Sun
High-order Tensor Pooling with Attention for Action Recognition. CoRR (2021)
Alexander Soen, Ke Sun
On the Variance of the Fisher Information for Deep Learning. NeurIPS (2021)
Yujun Chen, Ke Sun, Juhua Pu, Zhang Xiong, Xiangliang Zhang
GraPASA: Parametric graph embedding via siamese architecture. Inf. Sci. 512 (2020)
Marcel Keller, Ke Sun
Effectiveness of MPC-friendly Softmax Replacement. CoRR (2020)
Ke Sun, Frank Nielsen
Information-Geometric Set Embeddings (IGSE): From Sets to Probability Distributions. CoRR (2019)
Marcel Keller, Ke Sun
A Note on Our Submission to Track 4 of iDASH 2019. IACR Cryptol. ePrint Arch. 2019 (2019)
Ke Sun, Piotr Koniusz, Zhen Wang
Fisher-Bures Adversary Graph Convolutional Networks. UAI (2019)
Ke Sun, Frank Nielsen
Lightlike Neuromanifolds, Occam's Razor and Deep Learning. CoRR (2019)
Ke Sun, Piotr Koniusz, Zhen Wang
Fisher-Bures Adversary Graph Convolutional Networks. CoRR (2019)
Daniel Filonik, Tian Feng, Ke Sun, Richard Nock, Alex Collins, Tomasz Bednarz
Non-Euclidean Embeddings for Graph Analytics and Visualisation. SIGGRAPH Asia Posters (2019)
Marcel Keller, Ke Sun
A Note on Our Submission to Track 4 of iDASH 2019. CoRR (2019)
Frank Nielsen, Ke Sun
Guaranteed Deterministic Bounds on the total variation Distance between univariate mixtures. MLSP (2018)
Frank Nielsen, Ke Sun
On The Chain Rule Optimal Transport Distance. CoRR (2018)
Ke Sun
Intrinsic Universal Measurements of Non-linear Embeddings. CoRR (2018)
Marta Avalos, Richard Nock, Cheng Soon Ong, Julien Rouar, Ke Sun
Representation Learning of Compositional Data. NeurIPS (2018)
Frank Nielsen, Ke Sun
Guaranteed Deterministic Bounds on the Total Variation Distance between Univariate Mixtures. CoRR (2018)
Frank Nielsen, Ke Sun
q-Neurons: Neuron Activations based on Stochastic Jackson's Derivative Operators. CoRR (2018)
Uchenna Akujuobi, Ke Sun, Xiangliang Zhang
Mining top-k Popular Datasets via a Deep Generative Model. IEEE BigData (2018)
Frank Nielsen, Ke Sun
Combinatorial bounds on the α-divergence of univariate mixture models. ICASSP (2017)
Ke Sun, Frank Nielsen
Relative Fisher Information and Natural Gradient for Learning Large Modular Models. ICML (2017)
Ke Sun, Xiangliang Zhang
Coarse Grained Exponential Variational Autoencoders. CoRR (2017)
Frank Nielsen, Ke Sun, Stéphane Marchand-Maillet
On Hölder projective divergences. CoRR (2017)
Frank Nielsen, Ke Sun, Stéphane Marchand-Maillet
On Hölder Projective Divergences. Entropy 19 (3) (2017)
Frank Nielsen, Ke Sun, Stéphane Marchand-Maillet
k-Means Clustering with Hölder Divergences. GSI (2017)
Frank Nielsen, Ke Sun
Clustering in Hilbert simplex geometry. CoRR (2017)
Frank Nielsen, Ke Sun
Guaranteed Bounds on the Kullback-Leibler Divergence of Univariate Mixtures. IEEE Signal Process. Lett. 23 (11) (2016)
Frank Nielsen, Ke Sun
Guaranteed Bounds on Information-Theoretic Measures of Univariate Mixtures Using Piecewise Log-Sum-Exp Inequalities. Entropy 18 (12) (2016)
Ke Sun, Frank Nielsen
Relative Natural Gradient for Learning Large Complex Models. CoRR (2016)
Frank Nielsen, Ke Sun
Guaranteed bounds on the Kullback-Leibler divergence of univariate mixtures using piecewise log-sum-exp inequalities. CoRR (2016)
Ke Sun, Jun Wang, Alexandros Kalousis, Stéphane Marchand-Maillet
Information Geometry and Minimum Description Length Networks. ICML (2015)
Ke Sun, Jun Wang, Alexandros Kalousis, Stéphane Marchand-Maillet
Space-Time Local Embeddings. NIPS (2015)
Ke Sun, Hisham Mohamed, Stéphane Marchand-Maillet
Sparsity on Statistical Simplexes and Diversity in Social Ranking. ACML (2014)
Ke Sun, Stéphane Marchand-Maillet
An Information Geometry of Statistical Manifold Learning. ICML (2014)
Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis
Two-Stage Metric Learning. ICML (2014)
Farzad Farhadzadeh, Ke Sun, Sohrab Fredowsi
Efficient two stage decoding scheme to achieve content identification capacity. ICASSP (2014)
Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis
Two-Stage Metric Learning. CoRR (2014)
Ke Sun, Donn Morrison, Eric Bruno, Stéphane Marchand-Maillet
Learning Representative Nodes in Social Networks. PAKDD (2) (2013)
Ke Sun, Eric Bruno, Stéphane Marchand-Maillet
Unsupervised skeleton learning for manifold denoising. ICPR (2012)
Ke Sun, Eric Bruno, Stéphane Marchand-Maillet
Stochastic unfolding. MLSP (2012)
Ke Sun, Shikui Tu, David Yang Gao, Lei Xu
Canonical Dual Approach to Binary Factor Analysis. ICA (2009)
Ke Sun, Lei Xu
Bayesian Ying-Yang Learning on Orthogonal Binary Factor Analysis. ICANN (1) (2008)
Ke Sun, Fengshan Bai
Mining Weighted Association Rules without Preassigned Weights. IEEE Trans. Knowl. Data Eng. 20 (4) (2008)
Ke Sun, Hong Wang
A Composite Method to Extract Eye Contour. ACII (2005)