Taiji Suzuki
Identifiers
- name variant Taiji Suzuki 0.60 · backfill
Papers (44)
- How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis stat.ML · 2026 · author #6
- From Saddle Points Toward Global Minima: A Newton-Type Method on Wasserstein Space math.OC · 2026 · author #2
- Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine cs.LG · 2026 · author #6
- Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds cs.LG · 2026 · author #2
- The Mechanism of Weak-to-Strong Generalization: Feature Elicitation from Latent Knowledge stat.ML · 2026 · author #2
- DPRM: A Plug-in Doob h transform-induced Token-Ordering Module for Diffusion Language Models cs.LG · 2026 · author #6
- Provable Benefit of Curriculum in Transformer Tree-Reasoning Post-Training cs.LG · 2025 · author #7
- Gradient Noise Convolution (GNC): Smoothing Loss Function for Distributed Large-Batch SGD cs.LG · 2019 · author #2
- Adam Induces Implicit Weight Sparsity in Rectifier Neural Networks cs.LG · 2018 · author #2
- Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality stat.ML · 2018 · author #1
- Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation math.OC · 2018 · author #2
- Cross-domain Recommendation via Deep Domain Adaptation cs.LG · 2018 · author #5
- Functional Gradient Boosting based on Residual Network Perception stat.ML · 2018 · author #2
- Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models stat.ML · 2018 · author #2
- Stochastic Particle Gradient Descent for Infinite Ensembles stat.ML · 2017 · author #2
- Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables stat.ML · 2017 · author #2
- Fast learning rate of deep learning via a kernel perspective math.ST · 2017 · author #1
- Trimmed Density Ratio Estimation stat.ML · 2017 · author #3
- Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization math.OC · 2017 · author #2
- Learning Sparse Structural Changes in High-dimensional Markov Networks: A Review on Methodologies and Theories stat.ML · 2017 · author #3
- Generalized ridge estimator and model selection criterion in multivariate linear regression math.ST · 2016 · author #2
- Stochastic dual averaging methods using variance reduction techniques for regularized empirical risk minimization problems math.OC · 2016 · author #2
- Structure Learning of Partitioned Markov Networks stat.ML · 2015 · author #2
- Convergence rate of Bayesian tensor estimator: Optimal rate without restricted strong convexity stat.ML · 2014 · author #1
- Spectral norm of random tensors math.ST · 2014 · author #2
- Support Consistency of Direct Sparse-Change Learning in Markov Networks stat.ML · 2014 · author #2
- Stochastic Dual Coordinate Ascent with Alternating Direction Multiplier Method stat.ML · 2013 · author #1
- Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation stat.ML · 2013 · author #4
- Convex Tensor Decomposition via Structured Schatten Norm Regularization stat.ML · 2013 · author #2
- Density-Difference Estimation cs.LG · 2012 · author #3
- A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems stat.ML · 2012 · author #3
- Fast learning rate of multiple kernel learning: Trade-off between sparsity and smoothness stat.ML · 2012 · author #1
- Fast Learning Rate of Non-Sparse Multiple Kernel Learning and Optimal Regularization Strategies stat.ML · 2011 · author #1
- Relative Density-Ratio Estimation for Robust Distribution Comparison stat.ML · 2011 · author #2
- Fast Learning Rate of lp-MKL and its Minimax Optimality stat.ML · 2011 · author #1
- Sharp Convergence Rate and Support Consistency of Multiple Kernel Learning with Sparse and Dense Regularization stat.ML · 2011 · author #1
- Fast Convergence Rate of Multiple Kernel Learning with Elastic-net Regularization stat.ML · 2011 · author #1
- Regularization Strategies and Empirical Bayesian Learning for MKL stat.ML · 2010 · author #2
- f-divergence estimation and two-sample homogeneity test under semiparametric density-ratio models stat.ML · 2010 · author #2
- Sparsity-accuracy trade-off in MKL stat.ML · 2010 · author #2
- Condition Number Analysis of Kernel-based Density Ratio Estimation stat.ML · 2009 · author #2
- Super-Linear Convergence of Dual Augmented-Lagrangian Algorithm for Sparsity Regularized Estimation stat.ML · 2009 · author #2
- SpicyMKL stat.ML · 2009 · author #1
- Game theoretic derivation of discrete distributions and discrete pricing formulas math.PR · 2005 · author #2
Mentions
- 1304.6803 #4 · backfill · confidence 0.70 Taiji Suzuki
- 1303.6370 #2 · backfill · confidence 0.70 Taiji Suzuki
- 2605.24749 #6 · arxiv_oai · confidence 0.70 Taiji Suzuki
- 1207.0099 #3 · backfill · confidence 0.70 Taiji Suzuki
- 1204.6583 #3 · backfill · confidence 0.70 Taiji Suzuki
- 1203.0565 #1 · backfill · confidence 0.70 Taiji Suzuki
- 1111.3781 #1 · backfill · confidence 0.70 Taiji Suzuki
- 2605.20235 #6 · arxiv_oai · confidence 0.70 Taiji Suzuki
- 1106.4729 #2 · backfill · confidence 0.70 Taiji Suzuki
- 1103.5202 #1 · backfill · confidence 0.70 Taiji Suzuki
- 1103.5201 #1 · backfill · confidence 0.70 Taiji Suzuki
- 1103.0431 #1 · backfill · confidence 0.70 Taiji Suzuki
- 2605.17963 #2 · arxiv_oai · confidence 0.70 Taiji Suzuki
- 2605.15822 #2 · arxiv_oai · confidence 0.70 Taiji Suzuki
- 1011.3090 #2 · backfill · confidence 0.70 Taiji Suzuki
- 1010.4945 #2 · backfill · confidence 0.70 Taiji Suzuki
- 1001.2615 #2 · backfill · confidence 0.70 Taiji Suzuki
- 0912.2800 #2 · backfill · confidence 0.70 Taiji Suzuki
- 0911.4046 #2 · backfill · confidence 0.70 Taiji Suzuki
- 0909.5026 #1 · backfill · confidence 0.70 Taiji Suzuki
Frequent Coauthors
- Masashi Sugiyama 11 shared papers
- Ryota Tomioka 8 shared papers
- Atsushi Nitanda 6 shared papers
- Song Liu 6 shared papers
- Kenji Fukumizu 5 shared papers
- Takafumi Kanamori 5 shared papers
- Andi Han 3 shared papers
- Tomoya Murata 3 shared papers
- Wei Huang 3 shared papers
- Akiko Takeda 2 shared papers
- Dake Bu 2 shared papers
- Hau-San Wong 2 shared papers
- Qingfu Zhang 2 shared papers
- Akifumi Wachi 1 shared papers
- Akimichi Takemura 1 shared papers
- Akiyuki Tanizawa 1 shared papers
- Atsushi Yaguchi 1 shared papers
- Guoji Fu 1 shared papers
- Hayato Kobayashi 1 shared papers
- Heishiro Kanagawa 1 shared papers