2025
Plan and Budget: Effective and Efficient Test-Time Scaling on Large Language Model Reasoning.
CoRR, May, 2025
LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection.
CoRR, May, 2025
ConstellationNet: Reinventing Spatial Clustering through GNNs.
CoRR, March, 2025
Low-Light Aerial Imaging With Color and Monochrome Cameras.
IEEE Trans. Geosci. Remote. Sens., 2025
High probability bounds on AdaGrad for constrained weakly convex optimization.
J. Complex., 2025
Reasoning of Large Language Models over Knowledge Graphs with Super-Relations.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
2024
Convergence of projected subgradient method with sparse or low-rank constraints.
Adv. Comput. Math., August, 2024
Robust Domain Generalization for Multi-modal Object Recognition.
CoRR, 2024
When Heterophily Meets Heterogeneity: New Graph Benchmarks and Effective Methods.
CoRR, 2024
Beyond Night Visibility: Adaptive Multi-Scale Fusion of Infrared and Visible Images.
CoRR, 2024
Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review.
CoRR, 2024
PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network.
CoRR, 2024
Nonconvex Deterministic Matrix Completion by Projected Gradient Descent Methods.
CoRR, 2024
Revisiting Convergence of AdaGrad with Relaxed Assumptions.
Proceedings of the Uncertainty in Artificial Intelligence, 2024
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
FraudGT: A Simple, Effective, and Efficient Graph Transformer for Financial Fraud Detection.
Proceedings of the 5th ACM International Conference on AI in Finance, 2024
UnifiedGT: Towards a Universal Framework of Transformers in Large-Scale Graph Learning.
Proceedings of the IEEE International Conference on Big Data, 2024
2023
LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal.
IEEE Trans. Circuits Syst. Video Technol., November, 2023
Low-Light Image Enhancement via Stage-Transformer-Guided Network.
IEEE Trans. Circuits Syst. Video Technol., August, 2023
Lightweight Semi-supervised Network for Single Image Rain Removal.
Pattern Recognit., May, 2023
High Probability Convergence of Adam Under Unbounded Gradients and Affine Variance Noise.
CoRR, 2023
LDRM: Degradation Rectify Model for Low-light Imaging via Color-Monochrome Cameras.
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography.
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Proceedings of the Bildverarbeitung für die Medizin 2023, 2023
2022
DesnowFormer: an effective transformer-based image desnowing network.
Proceedings of the IEEE International Conference on Visual Communications and Image Processing, 2022
2020
Beetle Swarm Optimization Algorithm-Based Load Control with Electricity Storage.
J. Control. Sci. Eng., 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms.
J. Mach. Learn. Res., 2020
Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections.
J. Mach. Learn. Res., 2020
Iterative hard thresholding for compressed data separation.
J. Complex., 2020
2019
A Learning-Based Framework for Quantized Compressed Sensing.
IEEE Signal Process. Lett., 2019
2018
Online Learning Algorithms Can Converge Comparably Fast as Batch Learning.
IEEE Trans. Neural Networks Learn. Syst., 2018
Indoor Localization Based on Weighted Surfacing from Crowdsourced Samples.
Sensors, 2018
Generalization properties of doubly stochastic learning algorithms.
J. Complex., 2018
Kernel Conjugate Gradient Methods with Random Projections.
CoRR, 2018
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms.
CoRR, 2018
Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces.
CoRR, 2018
Modified Fejér sequences and applications.
Comput. Optim. Appl., 2018
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces.
Proceedings of the 35th International Conference on Machine Learning, 2018
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods.
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Optimal Rates for Multi-pass Stochastic Gradient Methods.
J. Mach. Learn. Res., 2017
Online pairwise learning algorithms with convex loss functions.
Inf. Sci., 2017
Optimal Rates for Learning with Nyström Stochastic Gradient Methods.
CoRR, 2017
Generalization Properties of Doubly Online Learning Algorithms.
CoRR, 2017
2016
Restricted q-Isometry Properties Adapted to Frames for Nonconvex l<sub>q</sub>-Analysis.
IEEE Trans. Inf. Theory, 2016
Iterative Regularization for Learning with Convex Loss Functions.
J. Mach. Learn. Res., 2016
Restricted $q$-Isometry Properties Adapted to Frames for Nonconvex $l_q$-Analysis.
CoRR, 2016
Optimal Learning for Multi-pass Stochastic Gradient Methods.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM.
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Learning theory of randomized Kaczmarz algorithm.
J. Mach. Learn. Res., 2015
2013
New Bounds for Restricted Isometry Constants With Coherent Tight Frames.
IEEE Trans. Signal Process., 2013
Compressed Data Separation With Redundant Dictionaries.
IEEE Trans. Inf. Theory, 2013
Nonuniform support recovery from noisy random measurements by Orthogonal Matching Pursuit.
J. Approx. Theory, 2013
Sparse Recovery with Coherent Tight Frame via Analysis Dantzig Selector and Analysis LASSO
CoRR, 2013
2011
Compressed Sensing with coherent tight frames via $l_q$-minimization for $0<q\leq1$
CoRR, 2011