1 citations · 1 across the 10 of their papers we have counts for
10 papers
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…
Chvátal-Gomory Rounding of Eigenvector Inequalities for QCQPs
Santanu S. Dey, Nan Jiang, Aleksandr Kazachkov +2
We introduce and analyze a class of valid inequalities for nonconvex quadratically constrained optimization problems (QCQPs) which we call Eigen-CG inequalities. These inequalities…
EGG-SR: Embedding Symbolic Equivalence into Symbolic Regression via Equality Graph
Nan Jiang, Ziyi Wang, Yexiang Xue
Symbolic regression seeks to uncover physical laws from experimental data by searching for closed-form expressions, which is an important task in AI-driven scientific discovery. Ye…
Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits
Jinzhao Li, Nan Jiang, Yexiang Xue
Satisfiability Modulo Counting (SMC) is a recently proposed general language to reason about problems integrating statistical and symbolic Artificial Intelligence. An SMC problem i…
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…
Vertical Symbolic Regression
Nan Jiang, Md Nasim, Yexiang Xue
Automating scientific discovery has been a grand goal of Artificial Intelligence (AI) and will bring tremendous societal impact. Learning symbolic expressions from experimental dat…
Racing Control Variable Genetic Programming for Symbolic Regression
Nan Jiang, Yexiang Xue
Symbolic regression, as one of the most crucial tasks in AI for science, discovers governing equations from experimental data. Popular approaches based on genetic programming, Mont…
Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration With Provable Guarantees
Jinzhao Li, Nan Jiang, Yexiang Xue
Satisfiability Modulo Counting (SMC) encompasses problems that require both symbolic decision-making and statistical reasoning. Its general formulation captures many real-world pro…