Pengkun Yang

Orcid: 0000-0002-2279-3692

According to our database1, Pengkun Yang authored at least 25 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Global Convergence of Federated Learning for Mixed Regression.
IEEE Trans. Inf. Theory, September, 2024

Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms.
CoRR, 2024

On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments.
CoRR, 2024

Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Deep Active Learning with Noise Stability.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Semi-supervised transfer learning with hierarchical self-regularization.
Pattern Recognit., December, 2023

Sampling for remote estimation of an Ornstein-Uhlenbeck process through channel with unknown delay statistics.
J. Commun. Networks, October, 2023

Age Optimal Sampling Under Unknown Delay Statistics.
IEEE Trans. Inf. Theory, February, 2023

A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points.
J. Mach. Learn. Res., 2023

Two Phases of Scaling Laws for Nearest Neighbor Classifiers.
CoRR, 2023

Federated Learning in the Presence of Adversarial Client Unavailability.
CoRR, 2023

On the best approximation by finite Gaussian mixtures.
Proceedings of the IEEE International Symposium on Information Theory, 2023

2022
Deep Active Learning with Noise Stability.
CoRR, 2022

Boosting Active Learning via Improving Test Performance.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points.
CoRR, 2021

Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks.
Proceedings of the Conference on Learning Theory, 2021

2020
Polynomial Methods in Statistical Inference: Theory and Practice.
Found. Trends Commun. Inf. Theory, 2020

Optimal estimation of high-dimensional Gaussian mixtures.
CoRR, 2020

2019
On Learning Over-parameterized Neural Networks: A Functional Approximation Prospective.
CoRR, 2019

On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Polynomial methods in statistical inference: Theory and practice
PhD thesis, 2018

2016
Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation.
IEEE Trans. Inf. Theory, 2016

2015
Optimal entropy estimation on large alphabets via best polynomial approximation.
Proceedings of the IEEE International Symposium on Information Theory, 2015

2013
Software defined radio implementation of signaling splitting in hyper-cellular network.
Proceedings of the second workshop on Software radio implementation forum, 2013

Per-packet load-balanced, low-latency routing for clos-based data center networks.
Proceedings of the Conference on emerging Networking Experiments and Technologies, 2013


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