Xiao, Lechao

1. Scaling Exponents Across Parameterizations and Optimizers
   2024/07/08 by Katie Everett, Everett, Katie, Lechao Xiao +19 · 2 voices · 20 citations
   #cs.LG
2. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models
   2023/12/11 by Avi Singh, John D. Co-Reyes, Singh, Avi +76 · 37 citations
   Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Natural Language Processing Techniques #Topic Modeling
3. Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
   2018/06/14 by Lechao Xiao, Yasaman Bahri, Xiao, Lechao +7 · 30 citations
   Computer Science · #Generative Adversarial Networks and Image Synthesis #Advanced Neural Network Applications #Human Pose and Action Recognition
4. Small-scale proxies for large-scale Transformer training instabilities
   2023/09/25 by Mitchell Wortsman, Peter J. Liu, Wortsman, Mitchell +29 · 27 citations
   Computer Science · Decision Sciences · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Forecasting Techniques and Applications #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG)
5. Bayesian Deep Convolutional Networks with Many Channels are Gaussian\n Processes
   2018/10/11 by Roman Novak, Novak, Roman, Lechao Xiao +16 · 22 citations
   Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Neural and Evolutionary Computing (cs.NE)
6. Dataset Distillation with Infinitely Wide Convolutional Networks
   2021/07/27 by Timothy Nguyen, Nguyen, Timothy, Roman Novak +5 · 16 citations
   Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
7. 4+3 Phases of Compute-Optimal Neural Scaling Laws
   2024/05/23 by Elliot Paquette, Courtney Paquette, Paquette, Elliot +5 · 21 citations
   Computer Science · #Neural Networks and Applications
8. Neural Tangents: Fast and Easy Infinite Neural Networks in Python
   2019/12/05 by Roman Novak, Novak, Roman, Lechao Xiao +11 · 12 citations
   Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning
9. Finite Versus Infinite Neural Networks: an Empirical Study
   2020/07/31 by Lee, Jaehoon, Schoenholz, Samuel S., Pennington, Jeffrey +4 · 6 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
10. Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks
    2020/01/16 by Wei Hu, Hu, Wei, Lechao Xiao +3 · 6 citations
    Computer Science · #Speech Recognition and Synthesis #Neural Networks and Applications #Gaussian Processes and Bayesian Inference
11. Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
    2025/07/02 by Shikai Qiu, Qiu, Shikai, Lechao Xiao +7 · 3 voices · 11 citations
    #cs.LG
12. Uniform estimates for bilinear Hilbert transform and bilinear maximal functions associated to polynomials
    2013/08/15 by Li, Xiaochun, Xiao, Lechao · 3 citations
    #Classical Analysis and ODEs (math.CA) #FOS: Mathematics
13. Rethinking Conventional Wisdom in Machine Learning: From Generalization to Scaling
    2024/09/23 by Xiao, Lechao · 6 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
14. The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks
    2020/06/25 by Wei Hu, Hu, Wei, Lechao Xiao +5 · 2 citations
    Computer Science · #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms #Neural Networks and Applications
15. Fast Neural Kernel Embeddings for General Activations
    2022/09/09 by Han, Insu, Zandieh, Amir, Lee, Jaehoon +3 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
16. Maximal Decay Inequalities for Trilinear oscillatory integrals of convolution type
    2015/11/17 by Gressman, Philip T., Xiao, Lechao · 1 citation
    #Classical Analysis and ODEs (math.CA) #FOS: Mathematics
17. Endpoint estimates for one-dimensional oscillatory integral operator
    2016/02/18 by Xiao, Lechao · 1 citation
    #42B20 #Classical Analysis and ODEs (math.CA) #FOS: Mathematics
18. Higher decay inequalities for multilinear oscillatory integrals
    2016/11/30 by Maxim Gilula, Philip T. Gressman, Gilula, Maxim +3 · 1 citation
    Mathematics · #42B20 #Advanced Harmonic Analysis Research #Classical Analysis and ODEs (math.CA) #FOS: Mathematics #Nonlinear Partial Differential Equations #Spectral Theory in Mathematical Physics
19. Disentangling Trainability and Generalization in Deep Neural Networks
    2019/12/30 by Xiao, Lechao, Jeffrey Pennington, Samuel S. Schoenholz +2 · 2 citations
    Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
20. Precise Learning Curves and Higher-Order Scaling Limits for Dot Product Kernel Regression
    2022/05/30 by Xiao, Lechao, Hu, Hong, Misiakiewicz, Theodor +2 · 1 citation
    #68T07 #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)