Skip to content
conftrace_

Wenjing Liao

9 papers · 2019–2025 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

Jump to papers ↓
+4 more ↓ 🌍 Conference Polyglot Β· Bronze πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze πŸ—ΊοΈ Taxonomy Completionist (14) 🐣 Hot Topic Early Bird
🧭 Keyword Pioneer πŸ† Keyword Champion (2) 🧬 Topic Evolution πŸ”₯ Unstoppable Β· Bronze

Venues

ICML (3) JMLR (3) NeurIPS (3)

Top co-authors

Minshuo Chen (6) Tuo Zhao (6) Hao Liu (4) Haoming Jiang (1) Siawpeng Er (1) Haizhao Yang (1) Jiahui Cheng (1) Tong Zhang (1) Alexander Havrilla (1) Mauro Maggioni (1)

Research topics

Machine Learning (9) Optimization & Theory Β· Machine Learning (8) Deep Learning (7) Architectures (6) Optimization & Theory Β· Deep Learning (5) Core Methods (4) Artificial Intelligence (1) Mathematics & Optimization (1) Core AI (1) Learning Types (1) Mathematics (1) Models (1)

Keywords

function approximation (5) deep neural network (3) manifold learning (3) approximation theory (3) nonparametric estimation (2) low-dimensional manifold (2) convolutional residual network (2) sample complexity (2) relu network (2) generalization error (2) manifold hypothesis (2) nonparametric regression (1) geometric analysis (1) intrinsic dimension (1) neural network theory (1) adversarial robustness (1) neural network optimization (1) low-dimensional structure (1) wavelet transform (1) approximation error (1)

Papers

Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation JMLR 2025 Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces JMLR 2024 Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data NeurIPS 2024 Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories ICML 2023 Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint ICML 2022 On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds NeurIPS 2022 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks ICML 2021 Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data JMLR 2019 Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds NeurIPS 2019