Issei Sato

Orcid: 0000-0002-5066-1435

According to our database1, Issei Sato authored at least 131 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training.
Trans. Mach. Learn. Res., 2024

Theoretical Analysis of Hierarchical Language Recognition and Generation by Transformers without Positional Encoding.
CoRR, 2024

On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding.
CoRR, 2024

Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective.
CoRR, 2024

Top-Down Bayesian Posterior Sampling for Sum-Product Networks.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Exploring Weight Balancing on Long-Tailed Recognition Problem.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Understanding Parameter Saliency via Extreme Value Theory.
CoRR, 2023

Initialization Bias of Fourier Neural Operator: Revisiting the Edge of Chaos.
CoRR, 2023

On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural Lagrangian Schrödinger Bridge: Diffusion Modeling for Population Dynamics.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Active Classification With Uncertainty Comparison Queries.
Neural Comput., 2022

Excess risk analysis for epistemic uncertainty with application to variational inference.
CoRR, 2022

Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection.
CoRR, 2022

Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey.
CoRR, 2022

Neural Lagrangian Schrödinger Bridge.
CoRR, 2022

Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Closer Look at Prototype Classifier for Few-shot Image Classification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Evaluation Methods for Representation Learning: A Survey.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum.
Proceedings of the International Conference on Machine Learning, 2022

Disentanglement Analysis with Partial Information Decomposition.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Predictive variational Bayesian inference as risk-seeking optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Pairwise Supervision Can Provably Elicit a Decision Boundary.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting.
Neural Comput., 2021

Semisupervised Ordinal Regression Based on Empirical Risk Minimization.
Neural Comput., 2021

Classification From Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization.
Neural Comput., 2021

Multilevel Monte Carlo Variational Inference.
J. Mach. Learn. Res., 2021

Accelerated Diffusion-Based Sampling by the Non-Reversible Dynamics with Skew-Symmetric Matrices.
Entropy, 2021

Abelian Neural Networks.
CoRR, 2021

Interactive Optimization of Generative Image Modelling using Sequential Subspace Search and Content-based Guidance.
Comput. Graph. Forum, 2021

Versatile anomaly detection method for medical images with semi-supervised flow-based generative models.
Int. J. Comput. Assist. Radiol. Surg., 2021

User interfaces for high-dimensional design problems: from theories to implementations.
Proceedings of the SIGGRAPH 2021: Special Interest Group on Computer Graphics and Interactive Techniques Conference, 2021

Toward Neural-Network-Guided Program Synthesis and Verification.
Proceedings of the Static Analysis - 28th International Symposium, 2021

Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Loss function based second-order Jensen inequality and its application to particle variational inference.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima.
Proceedings of the 9th International Conference on Learning Representations, 2021

Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Sequential gallery for interactive visual design optimization.
ACM Trans. Graph., 2020

Development of training environment for deep learning with medical images on supercomputer system based on asynchronous parallel Bayesian optimization.
J. Supercomput., 2020

Classification from Triplet Comparison Data.
Neural Comput., 2020

Weak approximation of transformed stochastic gradient MCMC.
Mach. Learn., 2020

Stable Weight Decay Regularization.
CoRR, 2020

Classification from Ambiguity Comparisons.
CoRR, 2020

Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia.
CoRR, 2020

LFD-ProtoNet: Prototypical Network Based on Local Fisher Discriminant Analysis for Few-shot Learning.
CoRR, 2020

γ-ABC: Outlier-Robust Approximate Bayesian Computation based on Robust Divergence Estimator.
CoRR, 2020

Similarity-based Classification: Connecting Similarity Learning to Binary Classification.
CoRR, 2020

Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time.
CoRR, 2020

A Diffusion Theory for Deep Learning Dynamics: Stochastic Gradient Descent Escapes From Sharp Minima Exponentially Fast.
CoRR, 2020

Anomaly detection in chest radiographs with a weakly supervised flow-based deep learning method.
CoRR, 2020

Novel platform for development, training, and validation of computer-assisted detection/diagnosis software.
Int. J. Comput. Assist. Radiol. Surg., 2020

Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis.
Proceedings of the 37th International Conference on Machine Learning, 2020

Few-shot Domain Adaptation by Causal Mechanism Transfer.
Proceedings of the 37th International Conference on Machine Learning, 2020

Accelerating the diffusion-based ensemble sampling by non-reversible dynamics.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Comparison Of Compressed Sensing And Dnn Based Reconstruction For Ghost Motion Imaging.
Proceedings of the IEEE International Conference on Image Processing, 2020

2019
Bayesian interpretation of SGD as Ito process.
CoRR, 2019

Interactive Subspace Exploration on Generative Image Modelling.
CoRR, 2019

Solving NP-Hard Problems on Graphs by Reinforcement Learning without Domain Knowledge.
CoRR, 2019

Use of Ghost Cytometry to Differentiate Cells with Similar Gross Morphologic Characteristics.
CoRR, 2019

On Learning from Ghost Imaging without Imaging.
CoRR, 2019

On Transformations in Stochastic Gradient MCMC.
CoRR, 2019

PAC-Bayes Analysis of Sentence Representation.
CoRR, 2019

Online Multiclass Classification Based on Prediction Margin for Partial Feedback.
CoRR, 2019

Multi-level Monte Carlo Variational Inference.
CoRR, 2019

Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization.
CoRR, 2019

Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Clipped Matrix Completion: A Remedy for Ceiling Effects.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Unsupervised Domain Adaptation Based on Source-Guided Discrepancy.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Bayesian Posterior Approximation via Greedy Particle Optimization.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Convex formulation of multiple instance learning from positive and unlabeled bags.
Neural Networks, 2018

Mining Words in the Minds of Second Language Learners for Learner-specific Word Difficulty.
J. Inf. Process., 2018

Stochastic Divergence Minimization for Biterm Topic Models.
IEICE Trans. Inf. Syst., 2018

Frank-Wolfe Stein Sampling.
CoRR, 2018

Variational Inference for Gaussian Processes with Panel Count Data.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Bayesian Optimization of HPC Systems for Energy Efficiency.
Proceedings of the High Performance Computing - 33rd International Conference, 2018

Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model.
Proceedings of the 35th International Conference on Machine Learning, 2018

Does Distributionally Robust Supervised Learning Give Robust Classifiers?
Proceedings of the 35th International Conference on Machine Learning, 2018

Variational Inference based on Robust Divergences.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Sequential line search for efficient visual design optimization by crowds.
ACM Trans. Graph., 2017

Averaged Collapsed Variational Bayes Inference.
J. Mach. Learn. Res., 2017

Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags.
CoRR, 2017

On the Model Shrinkage Effect of Gamma Process Edge Partition Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Expectation Propagation for t-Exponential Family Using q-Algebra.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Lung lesion detection in FDG-PET/CT with Gaussian process regression.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Evaluating the Variance of Likelihood-Ratio Gradient Estimators.
Proceedings of the 34th International Conference on Machine Learning, 2017

A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors.
Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016
Reparameterization trick for discrete variables.
CoRR, 2016

Robust supervised learning under uncertainty in dataset shift.
CoRR, 2016

Differential Privacy without Sensitivity.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Model-Based Approaches for Independence-Enhanced Recommendation.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Company recommendation for new graduates via implicit feedback multiple matrix factorization with Bayesian optimization.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Infinite Plaid Models for Infinite Bi-Clustering.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Bayesian Differential Privacy on Correlated Data.
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31, 2015

Locally Optimized Hashing for Nearest Neighbor Search.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

The Hybrid Nested/Hierarchical Dirichlet Process and its Application to Topic Modeling with Word Differentiation.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Collapsed Variational Bayes Inference of Infinite Relational Model.
CoRR, 2014

Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process.
Proceedings of the 31th International Conference on Machine Learning, 2014

Latent Confusion Analysis by Normalized Gamma Construction.
Proceedings of the 31th International Conference on Machine Learning, 2014

Formalizing Word Sampling for Vocabulary Prediction as Graph-based Active Learning.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2013
Quantum annealing for Dirichlet process mixture models with applications to network clustering.
Neurocomputing, 2013

Understanding seed selection in bootstrapping.
Proceedings of TextGraphs@EMNLP 2013: the 8th Workshop on Graph-based Methods for Natural Language Processing, 2013

Multi-armed Bandit Problem with Lock-up Periods.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Privacy-Preserving EM Algorithm for Clustering on Social Network.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2012

Practical collapsed variational bayes inference for hierarchical dirichlet process.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Rethinking Collapsed Variational Bayes Inference for LDA.
Proceedings of the 29th International Conference on Machine Learning, 2012

Learning from Crowds and Experts.
Proceedings of the 4th Human Computation Workshop, 2012

Reducing Wrong Labels in Distant Supervision for Relation Extraction.
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, July 8-14, 2012, Jeju Island, Korea, 2012

2011
Probabilistic Matrix Factorization Leveraging Contexts for Unsupervised Relation Extraction.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

Secure Clustering in Private Networks.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010
Succinct Semi-structured Data Mining Based on FREQT.
Inf. Media Technol., 2010

Person name disambiguation by bootstrapping.
Proceedings of the Proceeding of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2010

Mining Numbers in Text Using Suffix Arrays and Clustering Based on Dirichlet Process Mixture Models.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2010

Deterministic Single-Pass Algorithm for LDA.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Collusion-resistant privacy-preserving data mining.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Topic models with power-law using Pitman-Yor process.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management.
Proceedings of the CLEF 2010 LABs and Workshops, 2010

2009
Quantum Annealing for Variational Bayes Inference.
Proceedings of the UAI 2009, 2009

2008
Person Name Disambiguation in Web Pages Using Social Network, Compound Words and Latent Topics.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

2007
Semi-structure Mining Method for Text Mining with a Chunk-Based Dependency Structure.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2007

Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Bayesian Document Generative Model with Explicit Multiple Topics.
Proceedings of the EMNLP-CoNLL 2007, 2007

2006
Text Mining using PrefixSpan constrained by Item Interval and Item Attribute.
Proceedings of the 22nd International Conference on Data Engineering Workshops, 2006


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