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Tuo Zhao

Identifiers

  • name variant Tuo Zhao 0.60 · backfill

Papers (108)

  1. QUBRIC: Co-Designing Queries and Rubrics for RL Beyond Verifiable Rewards cs.CL · 2026 · author #10
  2. Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation cs.CL · 2026 · author #4
  3. Controllable and Verifiable Tool-Use Data Synthesis for Agentic Reinforcement Learning cs.AI · 2026 · author #11
  4. Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity cs.LG · 2026 · author #3
  5. BackPlay: Head-Only Look-Back Self-Correction for Diffusion Language Models cs.LG · 2026 · author #6
  6. ARMOR: High-Performance Semi-Structured Pruning via Adaptive Matrix Factorization cs.LG · 2025 · author #4
  7. SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process cs.LG · 2023 · author #6
  8. Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification cs.LG · 2023 · author #5
  9. Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer cs.CL · 2023 · author #5
  10. Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms cs.LG · 2023 · author #9
  11. Module-wise Adaptive Distillation for Multimodality Foundation Models cs.CV · 2023 · author #6
  12. Pivotal Estimation of Linear Discriminant Analysis in High Dimensions math.ST · 2023 · author #5
  13. Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories cs.LG · 2023 · author #5
  14. LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation cs.LG · 2023 · author #7
  15. Machine Learning Force Fields with Data Cost Aware Training q-bio.QM · 2023 · author #7
  16. AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning cs.CL · 2023 · author #8
  17. On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds stat.ML · 2023 · author #4
  18. HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers cs.CL · 2023 · author #6
  19. Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data cs.LG · 2023 · author #3
  20. Efficient Long Sequence Modeling via State Space Augmented Transformer cs.CL · 2022 · author #6
  21. High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization cs.LG · 2022 · author #4
  22. Less is More: Task-aware Layer-wise Distillation for Language Model Compression cs.CL · 2022 · author #6
  23. First-order Policy Optimization for Robust Markov Decision Process cs.LG · 2022 · author #3
  24. Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites cs.IR · 2022 · author #7
  25. DiP-GNN: Discriminative Pre-Training of Graph Neural Networks cs.LG · 2022 · author #6
  26. Differentially Private Estimation of Hawkes Process cs.LG · 2022 · author #3
  27. PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance cs.LG · 2022 · author #7
  28. Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint stat.ML · 2022 · author #6
  29. Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks cs.LG · 2022 · author #4
  30. A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks stat.ML · 2022 · author #3
  31. MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation cs.CL · 2022 · author #5
  32. CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing cs.CL · 2022 · author #5
  33. CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data cs.IR · 2022 · author #5
  34. Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably cs.LG · 2022 · author #4
  35. No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models cs.CL · 2022 · author #8
  36. Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity cs.LG · 2022 · author #3
  37. Block Policy Mirror Descent cs.LG · 2022 · author #3
  38. Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network cs.LG · 2022 · author #6
  39. Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces stat.ML · 2022 · author #4
  40. Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning cs.MA · 2021 · author #4
  41. Learning Generalizable Vision-Tactile Robotic Grasping Strategy for Deformable Objects via Transformer cs.RO · 2021 · author #6
  42. Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits cs.LG · 2021 · author #6
  43. Taming Sparsely Activated Transformer with Stochastic Experts cs.CL · 2021 · author #7
  44. Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect cs.LG · 2021 · author #3
  45. Adversarially Regularized Policy Learning Guided by Trajectory Optimization cs.RO · 2021 · author #3
  46. Self-Training with Differentiable Teacher cs.CL · 2021 · author #7
  47. ARCH: Efficient Adversarial Regularized Training with Caching cs.CL · 2021 · author #8
  48. Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks stat.ML · 2021 · author #3
  49. QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction cs.CL · 2021 · author #9
  50. Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data cs.LG · 2021 · author #4
  51. Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data cs.CL · 2021 · author #5
  52. Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization cs.LG · 2021 · author #7
  53. Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach cs.LG · 2021 · author #6
  54. COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction cs.LG · 2021 · author #3
  55. Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach cs.LG · 2021 · author #8
  56. Token-wise Curriculum Learning for Neural Machine Translation cs.CL · 2021 · author #7
  57. Reinforcement Learning for Adaptive Mesh Refinement cs.LG · 2021 · author #8
  58. Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization cs.LG · 2021 · author #5
  59. Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach cs.CL · 2021 · author #4
  60. A Hypergradient Approach to Robust Regression without Correspondence cs.LG · 2020 · author #6
  61. Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks cs.LG · 2020 · author #4
  62. Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data cs.CL · 2020 · author #5
  63. Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach cs.CL · 2020 · author #5
  64. How Important is the Train-Validation Split in Meta-Learning? cs.LG · 2020 · author #4
  65. Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers cs.LG · 2020 · author #6
  66. BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision cs.CL · 2020 · author #6
  67. The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R stat.ML · 2020 · author #2
  68. Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python stat.ML · 2020 · author #7
  69. The huge Package for High-dimensional Undirected Graph Estimation in R stat.ML · 2020 · author #1
  70. Towards Understanding Hierarchical Learning: Benefits of Neural Representations cs.LG · 2020 · author #4
  71. Deep Reinforcement Learning with Robust and Smooth Policy cs.LG · 2020 · author #5
  72. Transformer Hawkes Process cs.LG · 2020 · author #4
  73. Differentiable Top-k Operator with Optimal Transport cs.LG · 2020 · author #5
  74. Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? -- A Neural Tangent Kernel Perspective cs.LG · 2020 · author #4
  75. Distribution Approximation and Statistical Estimation Guarantees of Generative Adversarial Networks cs.LG · 2020 · author #4
  76. On Computation and Generalization of Generative Adversarial Imitation Learning cs.LG · 2020 · author #7
  77. SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization cs.CL · 2019 · author #6
  78. Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing cs.CL · 2019 · author #4
  79. On Generalization Bounds of a Family of Recurrent Neural Networks cs.LG · 2019 · author #3
  80. Towards Understanding the Importance of Shortcut Connections in Residual Networks cs.LG · 2019 · author #6
  81. Towards Understanding the Importance of Noise in Training Neural Networks cs.LG · 2019 · author #6
  82. Meta Learning with Relational Information for Short Sequences cs.LG · 2019 · author #4
  83. Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks : Function Approximation and Statistical Recovery cs.LG · 2019 · author #4
  84. Inductive Bias of Gradient Descent based Adversarial Training on Separable Data cs.LG · 2019 · author #4
  85. On Scalable and Efficient Computation of Large Scale Optimal Transport cs.LG · 2019 · author #4
  86. On Computation and Generalization of GANs with Spectrum Control cs.LG · 2018 · author #6
  87. Learning to Defend by Learning to Attack cs.LG · 2018 · author #5
  88. Provable Gaussian Embedding with One Observation stat.ML · 2018 · author #3
  89. On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond cs.LG · 2018 · author #5
  90. On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization cs.LG · 2018 · author #5
  91. Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization cs.LG · 2018 · author #5
  92. Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models stat.ML · 2018 · author #4
  93. Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization cs.LG · 2018 · author #4
  94. A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization cs.LG · 2018 · author #4
  95. Misspecified Nonconvex Statistical Optimization for Phase Retrieval stat.ML · 2017 · author #4
  96. Deep Hyperspherical Learning cs.LG · 2017 · author #6
  97. On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions stat.ML · 2017 · author #6
  98. Online Factorization and Partition of Complex Networks From Random Walks cs.LG · 2017 · author #3
  99. Homotopy Parametric Simplex Method for Sparse Learning cs.LG · 2017 · author #4
  100. Dropping Convexity for More Efficient and Scalable Online Multiview Learning cs.LG · 2017 · author #4
  101. Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization cs.LG · 2016 · author #7
  102. The Physical Systems Behind Optimization Algorithms cs.LG · 2016 · author #4
  103. On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization math.OC · 2016 · author #2
  104. On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About Its Nonsmooth Loss Function cs.LG · 2016 · author #7
  105. NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization math.OC · 2016 · author #3
  106. Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction cs.LG · 2016 · author #5
  107. Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory stat.ML · 2014 · author #1
  108. Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery stat.ML · 2013 · author #3

Mentions

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Frequent Coauthors