Cong Fang
Orcid: 0000-0002-5076-7897Affiliations:
- Shenzhen Research Institute of Big Data, China
- Peking University, Department of Machine Intelligence, Beijing, China
According to our database1,
Cong Fang
authored at least 52 papers
between 2015 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
IEEE Trans. Pattern Anal. Mach. Intell., June, 2025
Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression.
CoRR, February, 2025
Optimal Algorithms in Linear Regression under Covariate Shift: On the Importance of Precondition.
CoRR, February, 2025
Fundamental Computational Limits in Pursuing Invariant Causal Prediction and Invariance-Guided Regularization.
CoRR, January, 2025
SEPARATE: A Simple Low-rank Projection for Gradient Compression in Modern Large-scale Model Training Process.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
2024
Designing Universally-Approximating Deep Neural Networks: A First-Order Optimization Approach.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2024
CoRR, 2024
On the Algorithmic Bias of Aligning Large Language Models with RLHF: Preference Collapse and Matching Regularization.
CoRR, 2024
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning.
CoRR, 2024
INSIGHT: End-to-End Neuro-Symbolic Visual Reinforcement Learning with Language Explanations.
CoRR, 2024
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Accelerated Gradient Algorithms with Adaptive Subspace Search for Instance-Faster Optimization.
CoRR, 2023
CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity.
CoRR, 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
IEEE Trans. Inf. Theory, 2022
IEEE Trans. Pattern Anal. Mach. Intell., 2022
Springer, ISBN: 978-981-16-9839-2, 2022
2021
CoRR, 2021
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks.
Proceedings of the Conference on Learning Theory, 2021
2020
IEEE Trans. Signal Process., 2020
Proc. IEEE, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
How to Characterize The Landscape of Overparameterized Convolutional Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Springer, ISBN: 978-981-15-2909-2, 2020
2019
Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations.
CoRR, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
Accelerating Asynchronous Algorithms for Convex Optimization by Momentum Compensation.
CoRR, 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
Feature learning via partial differential equation with applications to face recognition.
Pattern Recognit., 2017
Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2015
A robust hybrid method for text detection in natural scenes by learning-based partial differential equations.
Neurocomputing, 2015