Qing Qu
33 papers · 2014–2025 · 7 conferences · across top CS/AI conferences
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NIPS (13)
ICML (12)
ICLR (4)
AISTATS (1)
CVPR (1)
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JMLR (1)
Top co-authors
Research topics
Keywords
nonconvex optimization
(4)
diffusion model
(4)
neural collapse
(4)
matrix factorization
(3)
sparse recovery
(3)
model compression
(3)
spherical constraint
(2)
low-dimensional subspace
(2)
representation learning
(2)
transfer learning
(2)
deep neural network
(2)
signal recovery
(2)
dictionary learning
(2)
simplex equiangular tight frame
(2)
feature learning
(2)
gradient descent
(2)
weight matrix
(2)
low-rank matrix recovery
(2)
batch normalization
(1)
compressive sensing
(1)
Papers
Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability
ICLR 2025
Attention-Only Transformers via Unrolled Subspace Denoising
ICML 2025
SITCOM: Step-wise Triple-Consistent Diffusion Sampling For Inverse Problems
ICML 2025
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination
JMLR 2025
Neural Collapse in Multi-label Learning with Pick-all-label Loss
ICML 2024
A Global Geometric Analysis of Maximal Coding Rate Reduction
ICML 2024
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
ICML 2024
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure
NIPS 2024
Efficient Low-Dimensional Compression of Overparameterized Models
AISTATS 2024
Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture
CVPR 2024
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
ICLR 2024
The Emergence of Reproducibility and Consistency in Diffusion Models
ICML 2024
Optimal Eye Surgeon: Finding image priors through sparse generators at initialization
ICML 2024
Generalized Neural Collapse for a Large Number of Classes
ICML 2024
Symmetric Matrix Completion with ReLU Sampling
ICML 2024
BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference
NIPS 2024
Image Reconstruction Via Autoencoding Sequential Deep Image Prior
NIPS 2024
Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing
NIPS 2024
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold
NIPS 2022
Are All Losses Created Equal: A Neural Collapse Perspective
NIPS 2022
Hidden State Variability of Pretrained Language Models Can Guide Computation Reduction for Transfer Learning
EMNLP 2022
Robust Training under Label Noise by Over-parameterization
ICML 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
ICML 2022
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery
NIPS 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features
NIPS 2021
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training
NIPS 2021
Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning
ICLR 2020
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization
NIPS 2020
Short and Sparse Deconvolution --- A Geometric Approach
ICLR 2020
A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution
NIPS 2019
Convolutional Phase Retrieval
NIPS 2017
Complete Dictionary Recovery Using Nonconvex Optimization
ICML 2015
Finding a sparse vector in a subspace: Linear sparsity using alternating directions
NIPS 2014