Publications (32)
Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling
Hongyi Ding, Mohammad Emtiyaz Khan, Issei Sato +1
On Transformations in Stochastic Gradient MCMC
Soma Yokoi, Takuma Otsuka, Issei Sato
On Learning from Ghost Imaging without Imaging
Issei Sato
Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model
Hideaki Imamura, Issei Sato, Masashi Sugiyama
Bayesian posterior approximation via greedy particle optimization
Futoshi Futami, Zhenghang Cui, Issei Sato +1
Unsupervised Domain Adaptation Based on Source-guided Discrepancy
Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao +3
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Variational Inference for Gaussian Process with Panel Count Data
Hongyi Ding, Young Lee, Issei Sato +1
Online Multiclass Classification Based on Prediction Margin for Partial Feedback
Takuo Kaneko, Issei Sato, Masashi Sugiyama
Generative Adversarial Nets from a Density Ratio Estimation Perspective
Masatoshi Uehara, Issei Sato, Masahiro Suzuki +2
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Convex Formulation of Multiple Instance Learning from Positive and Unlabeled Bags
Han Bao, Tomoya Sakai, Issei Sato +1
Gaussian Process Classification with Privileged Information by Soft-to-Hard Labeling Transfer
Ryosuke Kamesawa, Issei Sato, Masashi Sugiyama
Rethinking Collapsed Variational Bayes Inference for LDA
Issei Sato, Hiroshi Nakagawa
On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Iku Ohama, Issei Sato, Takuya Kida +1
Stochastic Divergence Minimization for Biterm Topic Model
Zhenghang Cui, Issei Sato, Masashi Sugiyama
Expectation Propagation for t-Exponential Family Using Q-Algebra
Futoshi Futami, Issei Sato, Masashi Sugiyama
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions
Yusuke Tsuzuku, Issei Sato
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
Weihua Hu, Gang Niu, Issei Sato +1
Clipped Matrix Completion: A Remedy for Ceiling Effects
Takeshi Teshima, Miao Xu, Issei Sato +1
PAC-Bayes Analysis of Sentence Representation
Kento Nozawa, Issei Sato
Classification from Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization
Takuya Shimada, Han Bao, Issei Sato +1
Use of Ghost Cytometry to Differentiate Cells with Similar Gross Morphologic Characteristics
Hiroaki Adachi, Yoko Kawamura, Keiji Nakagawa +7
Hybrid Quantum Annealing for Clustering Problems
Shu Tanaka, Ryo Tamura, Issei Sato +1
Quantum Annealing for Variational Bayes Inference
Issei Sato, Kenichi Kurihara, Shu Tanaka +2
Restricted Collapsed Draw: Accurate Sampling for Hierarchical Chinese Restaurant Process Hidden Markov Models
Takaki Makino, Shunsuke Takei, Issei Sato +1
Collapsed Variational Bayes Inference of Infinite Relational Model
Katsuhiko Ishiguro, Issei Sato, Naonori Ueda
Imaging cytometry without image reconstruction (ghost cytometry)
Sadao Ota, Ryoichi Horisaki, Yoko Kawamura +2
Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clustering
Issei Sato, Shu Tanaka, Kenichi Kurihara +2
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping
Xi Yang, Bojian Wu, Issei Sato +1
Variational Inference based on Robust Divergences
Futoshi Futami, Issei Sato, Masashi Sugiyama
Quantum Annealing for Variational Bayes Inference
Issei Sato, Kenichi Kurihara, Shu Tanaka +2