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Hechang Chen

4 papers hereh-index 181.2k citations64 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG4
same name
  • Hechang Chen — 16 papers, h 6
  • Hechang Chen — 2 papers, h 5
  • Hechang Chen — 2 papers, h 1
  • Hechang Chen — 2 papers, h 1
  • Hechang Chen — 1 paper, h 1
  • Hechang Chen — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedA Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning

1 citations · 1 across the 1 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026★ 1 cited

A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning

Siyuan Guo, Yanchao Sun, Jifeng Hu +5

Offline reinforcement learning (RL) provides a promising solution to learning an agent fully relying on a data-driven paradigm. However, constrained by the limited quality of the o…

cs.LG2024

Policy Dispersion in Non-Markovian Environment

Bohao Qu, Xiaofeng Cao, Jielong Yang +4

Markov Decision Process (MDP) presents a mathematical framework to formulate the learning processes of agents in reinforcement learning. MDP is limited by the Markovian assumption…

cs.LG2024

Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling

Sili Huang, Jifeng Hu, Zhejian Yang +5

Recent works have shown the remarkable superiority of transformer models in reinforcement learning (RL), where the decision-making problem is formulated as sequential generation. T…

cs.LG2024

In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought

Sili Huang, Jifeng Hu, Hechang Chen +2

In-context learning is a promising approach for offline reinforcement learning (RL) to handle online tasks, which can be achieved by providing task prompts. Recent works demonstrat…

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