4 citations · 5 across the 3 of their papers we have counts for
4 papers
MCMC Can See Can't See
Daniel Matsui Smola
It is folklore that passing "convergence" diagnostics does not guarantee that a Markov chain has converged. We prove this as an impossibility for any finite checklist of diagnostic…
PA2D-MORL: Pareto Ascent Directional Decomposition based Multi-Objective Reinforcement Learning
Tianmeng Hu, Biao Luo
Multi-objective reinforcement learning (MORL) provides an effective solution for decision-making problems involving conflicting objectives. However, achieving high-quality approxim…
RIDER: 3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion
Tianmeng Hu, Yongzheng Cui, Biao Luo +1
The inverse design of RNA three-dimensional (3D) structures is crucial for engineering functional RNAs in synthetic biology and therapeutics. While recent deep learning approaches…
Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning
Tianmeng Hu, Yongzheng Cui, Rui Tang +2
Value decomposition is a central approach in multi-agent reinforcement learning (MARL), enabling centralized training with decentralized execution by factorizing the global value f…