39 citations · 85 across the 16 of their papers we have counts for
16 papers
Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions
Tongxin Li, Yiheng Lin, Shaolei Ren +1
We study the tradeoff between consistency and robustness in the context of a single-trajectory time-varying Markov Decision Process (MDP) with untrusted machine-learned advice. Our…
Hierarchical Game for Coupled Power System with Energy Sharing and Transportation System
Dongxiang Yan, Tongxin Li, Changhong Zhao +2
The wide deployment of distributed renewable energy sources and electric vehicles can help mitigate climate crisis. This necessitates new business models in the power sector to hed…
Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity
Yiheng Lin, Yang Hu, Guannan Qu +2
We study Model Predictive Control (MPC) and propose a general analysis pipeline to bound its dynamic regret. The pipeline first requires deriving a perturbation bound for a finite-…
Equipping Black-Box Policies with Model-Based Advice for Stable Nonlinear Control
Tongxin Li, Ruixiao Yang, Guannan Qu +3
Machine-learned black-box policies are ubiquitous for nonlinear control problems. Meanwhile, crude model information is often available for these problems from, e.g., linear approx…
Towards Balanced Three-phase Charging: Phase Optimization in Adaptive Charging Networks
Zixin Ye, Tongxin Li, Steven H. Low
We study the problem of phase optimization for electric-vehicle (EV) charging. We formulate our problem as a non-convex mixed-integer programming problem whose objective is to mini…
An Improved Surrogate Method for Solving the Energy Storage Optimal Bidding Problem
Yue Chen, Wei Wei, Tongxin Li +3
Energy storage is expected to play an increasingly important role in mitigating variations that come along with the growing penetration of renewable energy. In this paper, we study…
Robustness and Consistency in Linear Quadratic Control with Untrusted Predictions
Tongxin Li, Ruixiao Yang, Guannan Qu +4
We study the problem of learning-augmented predictive linear quadratic control. Our goal is to design a controller that balances \textit{"consistency"}, which measures the competit…
Learning-Based Predictive Control via Real-Time Aggregate Flexibility
Tongxin Li, Bo Sun, Yue Chen +3
Aggregators have emerged as crucial tools for the coordination of distributed, controllable loads. To be used effectively, an aggregator must be able to communicate the available f…
Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging
Bo Sun, Ali Zeynali, Tongxin Li +3
We introduce and study a general version of the fractional online knapsack problem with multiple knapsacks, heterogeneous constraints on which items can be assigned to which knapsa…
Real-time Flexibility Feedback for Closed-loop Aggregator and System Operator Coordination
Tongxin Li, Steven H. Low, Adam Wierman
Aggregators have emerged as crucial tools for the coordination of distributed, controllable loads. However, to be used effectively, aggregators must be able to communicate the avai…
Decentralized Provision of Renewable Predictions within a Virtual Power Plant
Yue Chen, Tongxin Li, Changhong Zhao +1
The mushrooming of distributed energy resources turns end-users from passive price-takers to active market participants. To manage those massive proactive end-users efficiently, vi…
Learning Graphs from Linear Measurements: Fundamental Trade-offs and Applications
Tongxin Li, Lucien Werner, Steven H. Low
We consider a specific graph learning task: reconstructing a symmetric matrix that represents an underlying graph using linear measurements. We present a sparsity characterization…
Maximum Likelihood Upper Bounds on the Capacities of Discrete Information Stable Channels
Tongxin Li
Motivated by a greedy approach for generating {\it{information stable}} processes, we prove a universal maximum likelihood (ML) upper bound on the capacities of discrete informatio…
Quadratically Constrained Channels with Causal Adversaries
Tongxin Li, Bikash Kumar Dey, Sidharth Jaggi +2
We consider the problem of communication over a channel with a causal jamming adversary subject to quadratic constraints. A sender Alice wishes to communicate a message to a receiv…
Energy-efficient Decoders for Compressive Sensing: Fundamental Limits and Implementations
Tongxin Li, Mayank Bakshi, Pulkit Grover
The fundamental problem considered in this paper is "What is the \textit{energy} consumed for the implementation of a \emph{compressive sensing} decoding algorithm on a circuit?".…
Group Testing with Prior Statistics
Tongxin Li, Chun Lam Chan, Wenhao Huang +2
We consider a new group testing model wherein each item is a binary random variable defined by an a priori probability of being defective. We assume that each probability is small…