Issei Sato

Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment ICLR 2025 Theoretical Analysis of Hierarchical Language Recognition and Generation by Transformers without Positional Encoding ACL 2025 Benign Overfitting in Token Selection of Attention Mechanism ICML 2025 On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding ICML 2025 On the Optimal Memorization Capacity of Transformers ICLR 2025 Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective NIPS 2024 Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective NIPS 2024 Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? ICLR 2024 Exploring Weight Balancing on Long-Tailed Recognition Problem ICLR 2024 Neural Lagrangian Schr\"{o}dinger Bridge: Diffusion Modeling for Population Dynamics ICLR 2023 On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective NIPS 2023 Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective NIPS 2022 Pairwise Supervision Can Provably Elicit a Decision Boundary AISTATS 2022 Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum ICML 2022 Evaluation Methods for Representation Learning: A Survey IJCAI 2022 A Closer Look at Prototype Classifier for Few-shot Image Classification NIPS 2022 Predictive variational Bayesian inference as risk-seeking optimization AISTATS 2022 Disentanglement Analysis with Partial Information Decomposition ICLR 2022 Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning NIPS 2021 Loss function based second-order Jensen inequality and its application to particle variational inference NIPS 2021 γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator AISTATS 2021 Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain AISTATS 2021 A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima ICLR 2021 Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification ICML 2021 Multilevel Monte Carlo Variational Inference JMLR 2021 Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis ICML 2020 Few-shot Domain Adaptation by Causal Mechanism Transfer ICML 2020 Accelerating the diffusion-based ensemble sampling by non-reversible dynamics ICML 2020 Unsupervised Domain Adaptation Based on Source-Guided Discrepancy AAAI 2019 On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions CVPR 2019 Bayesian Posterior Approximation via Greedy Particle Optimization AAAI 2019 Clipped Matrix Completion: A Remedy for Ceiling Effects AAAI 2019 Does Distributionally Robust Supervised Learning Give Robust Classifiers? ICML 2018 Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018 Variational Inference based on Robust Divergences AISTATS 2018 Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks NIPS 2018 Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model ICML 2018 On the Model Shrinkage Effect of Gamma Process Edge Partition Models NIPS 2017 Evaluating the Variance of Likelihood-Ratio Gradient Estimators ICML 2017 Averaged Collapsed Variational Bayes Inference JMLR 2017 Expectation Propagation for t-Exponential Family Using q-Algebra NIPS 2017 A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors ACML 2017 Differential Privacy without Sensitivity NIPS 2016 Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process ICML 2014 Formalizing Word Sampling for Vocabulary Prediction as Graph-based Active Learning EMNLP 2014 Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP NIPS 2014 Latent Confusion Analysis by Normalized Gamma Construction ICML 2014 Understanding seed selection in bootstrapping EMNLP 2013 Multi-armed Bandit Problem with Lock-up Periods ACML 2013 Reducing Wrong Labels in Distant Supervision for Relation Extraction ACL 2012 Mining Words in the Minds of Second Language Learners: Learner-Specific Word Difficulty COLING 2012 Deterministic Single-Pass Algorithm for LDA NIPS 2010 Bayesian Document Generative Model with Explicit Multiple Topics EMNLP 2007 Bayesian Document Generative Model with Explicit Multiple Topics CONLL 2007