Issei Sato - RankMe

179 papers A* 46A 8B 5C 3Journal 95Unranked 22

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Formal Comparison Between Chain-of-Thought and Latent Thought. CoRR Kevin Xu, Issei Sato
2025	A*	`conf`	Benign Overfitting in Token Selection of Attention Mechanism. ICML Keitaro Sakamoto, Issei Sato
2025	J	`jnl`	Can Test-time Computation Mitigate Memorization Bias in Neural Symbolic Regression? CoRR Shun Sato, Issei Sato
2025	J	`jnl`	Explaining Grokking and Information Bottleneck through Neural Collapse Emergence. CoRR Keitaro Sakamoto, Issei Sato
2025	J	`jnl`	FairT2I: Mitigating Social Bias in Text-to-Image Generation via Large Language Model-Assisted Detection and Attribute Rebalancing. CoRR Jinya Sakurai, Issei Sato
2025	A*	`conf`	Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment. ICLR Naoya Hasegawa, Issei Sato
2025	A*	`conf`	On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding. ICML Kevin Xu, Issei Sato
2025	A*	`conf`	On the Optimal Memorization Capacity of Transformers. ICLR Tokio Kajitsuka, Issei Sato
2025	J	`jnl`	Prior Specification for Exposure-based Bayesian Matrix Factorization. Trans. Mach. Learn. Res. Zicong Zhu, Issei Sato
2025	—	`conf`	Theoretical Analysis of Hierarchical Language Recognition and Generation by Transformers without Positional Encoding. ACL (1) Daichi Hayakawa, Issei Sato
2025	J	`jnl`	To CoT or To Loop? A Formal Comparison Between Chain-of-Thought and Looped Transformers. CoRR Kevin Xu, Issei Sato
2025	J	`jnl`	Towards neural-network-guided program synthesis and verification. Formal Methods Syst. Des. Naoki Kobayashi, Taro Sekiyama, Issei Sato, Hiroshi Unno
2025	J	`jnl`	Understanding Generalization in Physics Informed Models through Affine Variety Dimensions. CoRR Takeshi Koshizuka, Issei Sato
2025	J	`jnl`	Understanding Why Adam Outperforms SGD: Gradient Heterogeneity in Transformers. CoRR Akiyoshi Tomihari, Issei Sato
2024	A*	`conf`	Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? ICLR Tokio Kajitsuka, Issei Sato
2024	J	`jnl`	Benign or Not-Benign Overfitting in Token Selection of Attention Mechanism. CoRR Keitaro Sakamoto, Issei Sato
2024	J	`jnl`	End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training. CoRR Keitaro Sakamoto, Issei Sato
2024	J	`jnl`	End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training. Trans. Mach. Learn. Res. Keitaro Sakamoto, Issei Sato
2024	A*	`conf`	Exploring Weight Balancing on Long-Tailed Recognition Problem. ICLR Naoya Hasegawa, Issei Sato
2024	J	`jnl`	Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment. CoRR Naoya Hasegawa, Issei Sato
2024	J	`jnl`	On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding. CoRR Kevin Xu, Issei Sato
2024	J	`jnl`	Optimal Memorization Capacity of Transformers. CoRR Tokio Kajitsuka, Issei Sato
2024	J	`jnl`	Theoretical Analysis of Hierarchical Language Recognition and Generation by Transformers without Positional Encoding. CoRR Daichi Hayakawa, Issei Sato
2024	A*	`conf`	Top-Down Bayesian Posterior Sampling for Sum-Product Networks. KDD Soma Yokoi, Issei Sato
2024	J	`jnl`	Top-Down Bayesian Posterior Sampling for Sum-Product Networks. CoRR Soma Yokoi, Issei Sato
2024	J	`jnl`	Understanding Knowledge Hijack Mechanism in In-context Learning through Associative Memory. CoRR Shuo Wang, Issei Sato
2024	A*	`conf`	Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective. NeurIPS Akiyoshi Tomihari, Issei Sato
2024	J	`jnl`	Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective. CoRR Akiyoshi Tomihari, Issei Sato
2024	A*	`conf`	Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective. NeurIPS Takeshi Koshizuka, Masahiro Fujisawa, Yusuke Tanaka, Issei Sato
2023	J	`jnl`	Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? CoRR Tokio Kajitsuka, Issei Sato
2023	J	`jnl`	Exploring Weight Balancing on Long-Tailed Recognition Problem. CoRR Naoya Hasegawa, Issei Sato
2023	J	`jnl`	Initialization Bias of Fourier Neural Operator: Revisiting the Edge of Chaos. CoRR Takeshi Koshizuka, Masahiro Fujisawa, Yusuke Tanaka, Issei Sato
2023	A*	`conf`	Neural Lagrangian Schrödinger Bridge: Diffusion Modeling for Population Dynamics. ICLR Takeshi Koshizuka, Issei Sato
2023	A*	`conf`	On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective. NeurIPS Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama
2023	J	`jnl`	Understanding Parameter Saliency via Extreme Value Theory. CoRR Shuo Wang, Issei Sato
2022	A*	`conf`	A Closer Look at Prototype Classifier for Few-shot Image Classification. NeurIPS Mingcheng Hou, Issei Sato
2022	J	`jnl`	Active Classification With Uncertainty Comparison Queries. Neural Comput. Zhenghang Cui, Issei Sato
2022	A*	`conf`	Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum. ICML Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
2022	A*	`conf`	Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective. NeurIPS Keitaro Sakamoto, Issei Sato
2022	J	`jnl`	Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective. CoRR Keitaro Sakamoto, Issei Sato
2022	A*	`conf`	Disentanglement Analysis with Partial Information Decomposition. ICLR Seiya Tokui, Issei Sato
2022	J	`jnl`	Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey. CoRR Kento Nozawa, Issei Sato
2022	A*	`conf`	Evaluation Methods for Representation Learning: A Survey. IJCAI Kento Nozawa, Issei Sato
2022	J	`jnl`	Excess risk analysis for epistemic uncertainty with application to variational inference. CoRR Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2022	J	`jnl`	Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection. CoRR Takahiro Suzuki, Shouhei Hanaoka, Issei Sato
2022	J	`jnl`	Neural Lagrangian Schrödinger Bridge. CoRR Takeshi Koshizuka, Issei Sato
2022	A	`conf`	Pairwise Supervision Can Provably Elicit a Decision Boundary. AISTATS Han Bao, Takuya Shimada, Liyuan Xu, Issei Sato, Masashi Sugiyama
2022	A	`conf`	Predictive variational Bayesian inference as risk-seeking optimization. AISTATS Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	A Closer Look at Prototype Classifier for Few-shot Image Classification. CoRR Mingcheng Hou, Issei Sato
2021	A*	`conf`	A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima. ICLR Zeke Xie, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Abelian Neural Networks. CoRR Kenshin Abe, Takanori Maehara, Issei Sato
2021	J	`jnl`	Accelerated Diffusion-Based Sampling by the Non-Reversible Dynamics with Skew-Symmetric Matrices. Entropy Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato
2021	J	`jnl`	Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting. Neural Comput. Zeke Xie, Fengxiang He, Shaopeng Fu, Issei Sato, Dacheng Tao, Masashi Sugiyama
2021	A*	`conf`	Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification. ICML Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification. CoRR Shida Lei, Nan Lu, Gang Niu, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Classification From Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization. Neural Comput. Takuya Shimada, Han Bao, Issei Sato, Masashi Sugiyama
2021	A	`conf`	Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain. AISTATS Takahiro Mimori, Keiko Sasada, Hirotaka Matsui, Issei Sato
2021	J	`jnl`	Disentanglement Analysis with Partial Information Decomposition. CoRR Seiya Tokui, Issei Sato
2021	J	`jnl`	Interactive Optimization of Generative Image Modelling using Sequential Subspace Search and Content-based Guidance. Comput. Graph. Forum Toby Long Hin Chong, I-Chao Shen, Issei Sato, Takeo Igarashi
2021	A*	`conf`	Loss function based second-order Jensen inequality and its application to particle variational inference. NeurIPS Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Loss function based second-order Jensen inequality and its application to particle variational inference. CoRR Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Multilevel Monte Carlo Variational Inference. J. Mach. Learn. Res. Masahiro Fujisawa, Issei Sato
2021	J	`jnl`	Semisupervised Ordinal Regression Based on Empirical Risk Minimization. Neural Comput. Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
2021	B	`conf`	Toward Neural-Network-Guided Program Synthesis and Verification. SAS Naoki Kobayashi, Taro Sekiyama, Issei Sato, Hiroshi Unno
2021	J	`jnl`	Toward Neural-Network-Guided Program Synthesis and Verification. CoRR Naoki Kobayashi, Taro Sekiyama, Issei Sato, Hiroshi Unno
2021	A*	`conf`	Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning. NeurIPS Kento Nozawa, Issei Sato
2021	J	`jnl`	Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning. CoRR Kento Nozawa, Issei Sato
2021	—	`conf`	User interfaces for high-dimensional design problems: from theories to implementations. SIGGRAPH Courses Yonghao Yue, Yuki Koyama, Issei Sato, Takeo Igarashi
2021	J	`jnl`	Versatile anomaly detection method for medical images with semi-supervised flow-based generative models. Int. J. Comput. Assist. Radiol. Surg. Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Issei Sato, Daisuke Sato, Naoto Hayashi, Osamu Abe
2021	A	`conf`	γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator. AISTATS Masahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama
2020	B	`conf`	A Comparison Of Compressed Sensing And Dnn Based Reconstruction For Ghost Motion Imaging. ICIP Mantaro Yamada, Hiroaki Adachi, Ryoichi Horisaki, Issei Sato
2020	J	`jnl`	A Diffusion Theory for Deep Learning Dynamics: Stochastic Gradient Descent Escapes From Sharp Minima Exponentially Fast. CoRR Zeke Xie, Issei Sato, Masashi Sugiyama
2020	A*	`conf`	Accelerating the diffusion-based ensemble sampling by non-reversible dynamics. ICML Futoshi Futami, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia. CoRR Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Anomaly detection in chest radiographs with a weakly supervised flow-based deep learning method. CoRR Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Issei Sato, Naoto Hayashi, Osamu Abe
2020	J	`jnl`	Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting. CoRR Zeke Xie, Fengxiang He, Shaopeng Fu, Issei Sato, Dacheng Tao, Masashi Sugiyama
2020	J	`jnl`	Classification from Ambiguity Comparisons. CoRR Zhenghang Cui, Issei Sato
2020	J	`jnl`	Classification from Triplet Comparison Data. Neural Comput. Zhenghang Cui, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Development of training environment for deep learning with medical images on supercomputer system based on asynchronous parallel Bayesian optimization. J. Supercomput. Yukihiro Nomura, Issei Sato, Toshihiro Hanawa, Shouhei Hanaoka, Takahiro Nakao, Tomomi Takenaga, Tetsuya Hoshino, Yuji Sekiya, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe
2020	J	`jnl`	Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain. CoRR Takahiro Mimori, Keiko Sasada, Hirotaka Matsui, Issei Sato
2020	A*	`conf`	Few-shot Domain Adaptation by Causal Mechanism Transfer. ICML Takeshi Teshima, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Few-shot Domain Adaptation by Causal Mechanism Transfer. CoRR Takeshi Teshima, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	LFD-ProtoNet: Prototypical Network Based on Local Fisher Discriminant Analysis for Few-shot Learning. CoRR Kei Mukaiyama, Issei Sato, Masashi Sugiyama
2020	A*	`conf`	Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis. ICML Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Novel platform for development, training, and validation of computer-assisted detection/diagnosis software. Int. J. Comput. Assist. Radiol. Surg. Yukihiro Nomura, Soichiro Miki, Naoto Hayashi, Shouhei Hanaoka, Issei Sato, Takeharu Yoshikawa, Yoshitaka Masutani, Osamu Abe
2020	J	`jnl`	Sequential Gallery for Interactive Visual Design Optimization. CoRR Yuki Koyama, Issei Sato, Masataka Goto
2020	J	`jnl`	Sequential gallery for interactive visual design optimization. ACM Trans. Graph. Yuki Koyama, Issei Sato, Masataka Goto
2020	J	`jnl`	Similarity-based Classification: Connecting Similarity Learning to Binary Classification. CoRR Han Bao, Takuya Shimada, Liyuan Xu, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Stable Weight Decay Regularization. CoRR Zeke Xie, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time. CoRR Hideaki Imamura, Nontawat Charoenphakdee, Futoshi Futami, Issei Sato, Junya Honda, Masashi Sugiyama
2020	J	`jnl`	Weak approximation of transformed stochastic gradient MCMC. Mach. Learn. Soma Yokoi, Takuma Otsuka, Issei Sato
2020	J	`jnl`	γ-ABC: Outlier-Robust Approximate Bayesian Computation based on Robust Divergence Estimator. CoRR Masahiro Fujisawa, Takeshi Teshima, Issei Sato
2019	A*	`conf`	Bayesian Posterior Approximation via Greedy Particle Optimization. AAAI Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama
2019	J	`jnl`	Bayesian interpretation of SGD as Ito process. CoRR Soma Yokoi, Issei Sato
2019	J	`jnl`	Classification from Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization. CoRR Takuya Shimada, Han Bao, Issei Sato, Masashi Sugiyama
2019	J	`jnl`	Classification from Triplet Comparison Data. CoRR Zhenghang Cui, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
2019	A*	`conf`	Clipped Matrix Completion: A Remedy for Ceiling Effects. AAAI Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama
2019	—	`conf`	Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping. CVPR Workshops Xi Yang, Bojian Wu, Issei Sato, Takeo Igarashi
2019	J	`jnl`	Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping. CoRR Xi Yang, Bojian Wu, Issei Sato, Takeo Igarashi
2019	J	`jnl`	Interactive Subspace Exploration on Generative Image Modelling. CoRR Toby Long Hin Chong, I-Chao Shen, Issei Sato, Takeo Igarashi
2019	J	`jnl`	Multi-level Monte Carlo Variational Inference. CoRR Masahiro Fujisawa, Issei Sato
2019	J	`jnl`	Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis. CoRR Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
2019	J	`jnl`	On Learning from Ghost Imaging without Imaging. CoRR Issei Sato
2019	J	`jnl`	On Transformations in Stochastic Gradient MCMC. CoRR Soma Yokoi, Takuma Otsuka, Issei Sato
2019	A*	`conf`	On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions. CVPR Yusuke Tsuzuku, Issei Sato
2019	J	`jnl`	Online Multiclass Classification Based on Prediction Margin for Partial Feedback. CoRR Takuo Kaneko, Issei Sato, Masashi Sugiyama
2019	J	`jnl`	PAC-Bayes Analysis of Sentence Representation. CoRR Kento Nozawa, Issei Sato
2019	J	`jnl`	Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization. CoRR Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
2019	J	`jnl`	Solving NP-Hard Problems on Graphs by Reinforcement Learning without Domain Knowledge. CoRR Kenshin Abe, Zijian Xu, Issei Sato, Masashi Sugiyama
2019	A*	`conf`	Unsupervised Domain Adaptation Based on Source-Guided Discrepancy. AAAI Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama
2019	J	`jnl`	Use of Ghost Cytometry to Differentiate Cells with Similar Gross Morphologic Characteristics. CoRR Hiroaki Adachi, Yoko Kawamura, Keiji Nakagawa, Ryoichi Horisaki, Issei Sato, Satoko Yamaguchi, Katsuhito Fujiu, Kayo Waki, Hiroyuki Noji, Sadao Ota
2018	A*	`conf`	Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model. ICML Hideaki Imamura, Issei Sato, Masashi Sugiyama
2018	J	`jnl`	Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model. CoRR Hideaki Imamura, Issei Sato, Masashi Sugiyama
2018	A	`conf`	Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling. AISTATS Hongyi Ding, Mohammad Emtiyaz Khan, Issei Sato, Masashi Sugiyama
2018	C	`conf`	Bayesian Optimization of HPC Systems for Energy Efficiency. ISC Takashi Miyazaki, Issei Sato, Nobuyuki Shimizu
2018	J	`jnl`	Clipped Matrix Completion: a Remedy for Ceiling Effects. CoRR Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama
2018	J	`jnl`	Convex formulation of multiple instance learning from positive and unlabeled bags. Neural Networks Han Bao, Tomoya Sakai, Issei Sato, Masashi Sugiyama
2018	A*	`conf`	Does Distributionally Robust Supervised Learning Give Robust Classifiers? ICML Weihua Hu, Gang Niu, Issei Sato, Masashi Sugiyama
2018	J	`jnl`	Frank-Wolfe Stein Sampling. CoRR Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama
2018	A*	`conf`	Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks. NeurIPS Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
2018	J	`jnl`	Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks. CoRR Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
2018	A*	`conf`	Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition. KDD Issei Sato, Yukihiro Nomura, Shouhei Hanaoka, Soichiro Miki, Naoto Hayashi, Osamu Abe, Yoshitaka Masutani
2018	J	`jnl`	Mining Words in the Minds of Second Language Learners for Learner-specific Word Difficulty. J. Inf. Process. Yo Ehara, Issei Sato, Hidekazu Oiwa, Hiroshi Nakagawa
2018	J	`jnl`	On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions. CoRR Yusuke Tsuzuku, Issei Sato
2018	J	`jnl`	Stochastic Divergence Minimization for Biterm Topic Models. IEICE Trans. Inf. Syst. Zhenghang Cui, Issei Sato, Masashi Sugiyama
2018	J	`jnl`	Unsupervised Domain Adaptation Based on Source-guided Discrepancy. CoRR Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama
2018	A	`conf`	Variational Inference based on Robust Divergences. AISTATS Futoshi Futami, Issei Sato, Masashi Sugiyama
2018	A	`conf`	Variational Inference for Gaussian Processes with Panel Count Data. UAI Hongyi Ding, Young Lee, Issei Sato, Masashi Sugiyama
2017	C	`conf`	A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. ACML Zeke Xie, Issei Sato
2017	J	`jnl`	A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. CoRR Zeke Xie, Issei Sato
2017	J	`jnl`	Averaged Collapsed Variational Bayes Inference. J. Mach. Learn. Res. Katsuhiko Ishiguro, Issei Sato, Naonori Ueda
2017	A*	`conf`	Evaluating the Variance of Likelihood-Ratio Gradient Estimators. ICML Seiya Tokui, Issei Sato
2017	—	`conf`	Expectation Propagation for t-Exponential Family Using q-Algebra. NIPS Futoshi Futami, Issei Sato, Masashi Sugiyama
2017	—	`conf`	Lung lesion detection in FDG-PET/CT with Gaussian process regression. Computer-Aided Diagnosis Ryosuke Kamesawa, Issei Sato, Shouhei Hanaoka, Yukihiro Nomura, Mitsutaka Nemoto, Naoto Hayashi, Masashi Sugiyama
2017	—	`conf`	On the Model Shrinkage Effect of Gamma Process Edge Partition Models. NIPS Iku Ohama, Issei Sato, Takuya Kida, Hiroki Arimura
2017	J	`jnl`	Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags. CoRR Han Bao, Tomoya Sakai, Issei Sato, Masashi Sugiyama
2017	J	`jnl`	Sequential line search for efficient visual design optimization by crowds. ACM Trans. Graph. Yuki Koyama, Issei Sato, Daisuke Sakamoto, Takeo Igarashi
2016	—	`conf`	Company recommendation for new graduates via implicit feedback multiple matrix factorization with Bayesian optimization. IEEE BigData Masahiro Kazama, Issei Sato, Haruaki Yatabe, Tairiku Ogihara, Tetsuro Onishi, Hiroshi Nakagawa
2016	—	`conf`	Differential Privacy without Sensitivity. NIPS Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa
2016	A*	`conf`	Infinite Plaid Models for Infinite Bi-Clustering. AAAI Katsuhiko Ishiguro, Issei Sato, Masahiro Nakano, Akisato Kimura, Naonori Ueda
2016	—	`conf`	Model-Based Approaches for Independence-Enhanced Recommendation. ICDM Workshops Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Issei Sato
2016	J	`jnl`	Reparameterization trick for discrete variables. CoRR Seiya Tokui, Issei Sato
2016	J	`jnl`	Robust supervised learning under uncertainty in dataset shift. CoRR Weihua Hu, Issei Sato, Masashi Sugiyama
2015	—	`conf`	Bayesian Differential Privacy on Correlated Data. SIGMOD Conference Bin Yang, Issei Sato, Hiroshi Nakagawa
2015	—	`conf`	Locally Optimized Hashing for Nearest Neighbor Search. PAKDD (2) Seiya Tokui, Issei Sato, Hiroshi Nakagawa
2015	A*	`conf`	Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation. KDD Issei Sato, Hiroshi Nakagawa
2015	A*	`conf`	The Hybrid Nested/Hierarchical Dirichlet Process and its Application to Topic Modeling with Word Differentiation. AAAI Tengfei Ma, Issei Sato, Hiroshi Nakagawa
2014	—	`conf`	Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP. NIPS Shinichi Nakajima, Issei Sato, Masashi Sugiyama, Kazuho Watanabe, Hiroko Kobayashi
2014	A*	`conf`	Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process. ICML Issei Sato, Hiroshi Nakagawa
2014	J	`jnl`	Collapsed Variational Bayes Inference of Infinite Relational Model. CoRR Katsuhiko Ishiguro, Issei Sato, Naonori Ueda
2014	A*	`conf`	Formalizing Word Sampling for Vocabulary Prediction as Graph-based Active Learning. EMNLP Yo Ehara, Yusuke Miyao, Hidekazu Oiwa, Issei Sato, Hiroshi Nakagawa
2014	A*	`conf`	Latent Confusion Analysis by Normalized Gamma Construction. ICML Issei Sato, Hisashi Kashima, Hiroshi Nakagawa
2014	J	`jnl`	Quantum Annealing for Variational Bayes Inference. CoRR Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa, Seiji Miyashita
2013	C	`conf`	Multi-armed Bandit Problem with Lock-up Periods. ACML Junpei Komiyama, Issei Sato, Hiroshi Nakagawa
2013	J	`jnl`	Quantum annealing for Dirichlet process mixture models with applications to network clustering. Neurocomputing Issei Sato, Shu Tanaka, Kenichi Kurihara, Seiji Miyashita, Hiroshi Nakagawa
2013	—	`conf`	Understanding seed selection in bootstrapping. TextGraphs@EMNLP Yo Ehara, Issei Sato, Hidekazu Oiwa, Hiroshi Nakagawa
2012	—	`conf`	Learning from Crowds and Experts. HCOMP@AAAI Hiroshi Kajino, Yuta Tsuboi, Issei Sato, Hisashi Kashima
2012	B	`conf`	Mining Words in the Minds of Second Language Learners: Learner-Specific Word Difficulty. COLING Yo Ehara, Issei Sato, Hidekazu Oiwa, Hiroshi Nakagawa
2012	A*	`conf`	Practical collapsed variational bayes inference for hierarchical dirichlet process. KDD Issei Sato, Kenichi Kurihara, Hiroshi Nakagawa
2012	—	`conf`	Privacy-Preserving EM Algorithm for Clustering on Social Network. PAKDD (1) Bin Yang, Issei Sato, Hiroshi Nakagawa
2012	—	`conf`	Reducing Wrong Labels in Distant Supervision for Relation Extraction. ACL (1) Shingo Takamatsu, Issei Sato, Hiroshi Nakagawa
2012	A*	`conf`	Rethinking Collapsed Variational Bayes Inference for LDA. ICML Issei Sato, Hiroshi Nakagawa
2011	—	`conf`	Probabilistic Matrix Factorization Leveraging Contexts for Unsupervised Relation Extraction. PAKDD (1) Shingo Takamatsu, Issei Sato, Hiroshi Nakagawa
2011	A*	`conf`	Secure Clustering in Private Networks. ICDM Bin Yang, Issei Sato, Hiroshi Nakagawa
2010	A*	`conf`	Collusion-resistant privacy-preserving data mining. KDD Bin Yang, Hiroshi Nakagawa, Issei Sato, Jun Sakuma
2010	—	`conf`	Deterministic Single-Pass Algorithm for LDA. NIPS Issei Sato, Kenichi Kurihara, Hiroshi Nakagawa
2010	—	`conf`	ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management. CLEF (Notebook Papers/LABs/Workshops) Minoru Yoshida, Shin Matsushima, Shingo Ono, Issei Sato, Hiroshi Nakagawa
2010	—	`conf`	Mining Numbers in Text Using Suffix Arrays and Clustering Based on Dirichlet Process Mixture Models. PAKDD (2) Minoru Yoshida, Issei Sato, Hiroshi Nakagawa, Akira Terada
2010	A*	`conf`	Person name disambiguation by bootstrapping. SIGIR Minoru Yoshida, Masaki Ikeda, Shingo Ono, Issei Sato, Hiroshi Nakagawa
2010	J	`jnl`	Succinct Semi-structured Data Mining Based on FREQT. Inf. Media Technol. Issei Sato, Hiroshi Nakagawa
2010	A*	`conf`	Topic models with power-law using Pitman-Yor process. KDD Issei Sato, Hiroshi Nakagawa
2009	J	`jnl`	Quantum Annealing for Variational Bayes Inference CoRR Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa, Seiji Miyashita
2009	A	`conf`	Quantum Annealing for Variational Bayes Inference. UAI Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa, Seiji Miyashita
2008	A*	`conf`	Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model. KDD Issei Sato, Minoru Yoshida, Hiroshi Nakagawa
2008	B	`conf`	Person Name Disambiguation in Web Pages Using Social Network, Compound Words and Latent Topics. PAKDD Shingo Ono, Issei Sato, Minoru Yoshida, Hiroshi Nakagawa
2007	—	`conf`	Bayesian Document Generative Model with Explicit Multiple Topics. EMNLP-CoNLL Issei Sato, Hiroshi Nakagawa
2007	A*	`conf`	Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior. KDD Issei Sato, Hiroshi Nakagawa
2007	B	`conf`	Semi-structure Mining Method for Text Mining with a Chunk-Based Dependency Structure. PAKDD Issei Sato, Hiroshi Nakagawa
2006	—	`conf`	Text Mining using PrefixSpan constrained by Item Interval and Item Attribute. ICDE Workshops Issei Sato, Yu Hirate, Hayato Yamana