activity
20182023
most citedReinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges

422 citations · 673 across the 48 of their papers we have counts for

collaborators

48 papers

math.OC2023★ 3 cited

Carbon-Aware Optimal Power Flow

Xin Chen, Andy Sun, Wenbo Shi +1

To facilitate effective decarbonization of the electric power sector, this paper introduces the generic Carbon-aware Optimal Power Flow (C-OPF) method for power system decision-mak…

math.OC2023★ 1 cited

Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity

Runyu Zhang, Yang Hu, Na Li

Robust Markov Decision Processes (MDPs) and risk-sensitive MDPs are both powerful tools for making decisions in the presence of uncertainties. Previous efforts have aimed to establ…

cs.CL2023★ 1 cited

Ultra-Fine Entity Typing with Prior Knowledge about Labels: A Simple Clustering Based Strategy

Na Li, Zied Bouraoui, Steven Schockaert

Ultra-fine entity typing (UFET) is the task of inferring the semantic types, from a large set of fine-grained candidates, that apply to a given entity mention. This task is especia…

cs.CL2023★ 1 cited

Distilling Semantic Concept Embeddings from Contrastively Fine-Tuned Language Models

Na Li, Hanane Kteich, Zied Bouraoui +1

Learning vectors that capture the meaning of concepts remains a fundamental challenge. Somewhat surprisingly, perhaps, pre-trained language models have thus far only enabled modest…

cs.GT2023★ 1 cited

Markov Games with Decoupled Dynamics: Price of Anarchy and Sample Complexity

Runyu Zhang, Yuyang Zhang, Rohit Konda +3

This paper studies the finite-time horizon Markov games where the agents' dynamics are decoupled but the rewards can possibly be coupled across agents. The policy class is restrict…

math.OC2023★ 2 cited

Continuous-Time Zeroth-Order Dynamics with Projection Maps: Model-Free Feedback Optimization with Safety Guarantees

Xin Chen, Jorge I. Poveda, Na Li

This paper introduces a class of model-free feedback methods for solving generic constrained optimization problems where the specific mathematical forms of the objective and constr…