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Approximating Pareto Frontiers in Stochastic Multi-Objective Optimization via Hashing and Randomization
Jinzhao Li, Nan Jiang, Yexiang Xue
Stochastic Multi-Objective Optimization (SMOO) is critical for decision-making trading off multiple potentially conflicting objectives in uncertain environments. SMOO aims at ident…
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching
Nan Jiang, Md Nasim, Yexiang Xue
The symbolic discovery of Ordinary Differential Equations (ODEs) from trajectory data plays a pivotal role in AI-driven scientific discovery. Existing symbolic methods predominantl…
A Tighter Convergence Proof of Reverse Experience Replay
Nan Jiang, Jinzhao Li, Yexiang Xue
In reinforcement learning, Reverse Experience Replay (RER) is a recently proposed algorithm that attains better sample complexity than the classic experience replay method. RER req…
Vertical Symbolic Regression via Deep Policy Gradient
Nan Jiang, Md Nasim, Yexiang Xue
Vertical Symbolic Regression (VSR) recently has been proposed to expedite the discovery of symbolic equations with many independent variables from experimental data. VSR reduces th…