Taehyun Cho

According to our database¹, Taehyun Cho authored at least 16 papers between 2020 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2026

Probabilistic Smoothing with Ratio-Monotone Transforms for Global Optimization.

[BibT_eX]

[DOI]

CoRR, May, 2026

Why Latent Actions Fail, and How to Prevent It.

[BibT_eX]

[DOI]

CoRR, May, 2026

MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction.

[BibT_eX]

[DOI]

CoRR, February, 2026

Learning graph based individual intrinsic reward for multi-agent reinforcement learning.

[BibT_eX]

[DOI]

ICT Express, 2026

2025

Learning Generalizable Visuomotor Policy through Dynamics-Alignment.

[BibT_eX]

[DOI]

CoRR, October, 2025

Pareto Optimal Risk-Agnostic Distributional Bandits with Heavy-Tail Rewards.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Policy-labeled Preference Learning: Is Preference Enough for RLHF?

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Tractable and Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation.

[BibT_eX]

[DOI]

CoRR, 2024

Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

On the Convergence of Continual Learning with Adaptive Methods.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Optimized Shallow Neural Networks for Sum-Rate Maximization in Energy Harvesting Downlink Multiuser NOMA Systems.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2021

Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

An Efficient Neural Network Architecture for Rate Maximization in Energy Harvesting Downlink Channels.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2020

Taehyun Cho

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