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ORCIDAdam Wierman
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- affiliation: California Institute of Technology, Pasadena, CA, USA
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2020 – today
- 2023
[j107]Yorie Nakahira
, Andrés Ferragut, Adam Wierman:
Generalized Exact Scheduling: A Minimal-Variance Distributed Deadline Scheduler. Oper. Res. 71(2): 433-470 (2023)- [j106]Daan Rutten, Nicolas Christianson, Debankur Mukherjee, Adam Wierman:
Smoothed Online Optimization with Unreliable Predictions. Proc. ACM Meas. Anal. Comput. Syst. 7(1): 12:1-12:36 (2023) - [j105]Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman:
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. Proc. ACM Meas. Anal. Comput. Syst. 7(1): 13:1-13:51 (2023) - [j104]Jing Yu, Dimitar Ho, Adam Wierman:
Online Adversarial Stabilization of Unknown Networked Systems. Proc. ACM Meas. Anal. Comput. Syst. 7(1): 26:1-26:43 (2023) - [j103]Sungho Shin, Yiheng Lin, Guannan Qu, Adam Wierman, Mihai Anitescu:
Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems. SIAM J. Control. Optim. 61(3): 1113-1135 (2023) - [j102]Chen Liang, Linqi Guo, Alessandro Zocca, Steven H. Low, Adam Wierman:
Adaptive Network Response to Line Failures in Power Systems. IEEE Trans. Control. Netw. Syst. 10(1): 333-344 (2023) - [j101]Shih-Hao Tseng, SooJean Han, Adam Wierman:
Trading Throughput for Freshness: Freshness-aware Traffic Engineering and In-Network Freshness Control. ACM Trans. Model. Perform. Evaluation Comput. Syst. 8(1-2): 1-26 (2023) - [j100]Yue Chen, Changhong Zhao, Steven H. Low, Adam Wierman:
An Energy Sharing Mechanism Considering Network Constraints and Market Power Limitation. IEEE Trans. Smart Grid 14(2): 1027-1041 (2023) - [c120]Nicolas Christianson, Junxuan Shen, Adam Wierman:
Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems. AISTATS 2023: 9377-9399 - [c119]Xutong Liu, Jinhang Zuo, Siwei Wang, John C. S. Lui, Mohammad Hajiesmaili, Adam Wierman, Wei Chen:
Contextual Combinatorial Bandits with Probabilistically Triggered Arms. ICML 2023: 22559-22593 - [c118]Yingying Li, James A. Preiss, Na Li, Yiheng Lin, Adam Wierman, Jeff S. Shamma:
Online switching control with stability and regret guarantees. L4DC 2023: 1138-1151 - [c117]Bo Sun, Lin Yang, Mohammad H. Hajiesmaili, Adam Wierman, John C. S. Lui, Don Towsley, Danny H. K. Tsang:
The Online Knapsack Problem with Departures. SIGMETRICS (Abstracts) 2023: 59-60 - [c116]Daan Rutten, Nicolas Christianson, Debankur Mukherjee, Adam Wierman:
Smoothed Online Optimization with Unreliable Predictions. SIGMETRICS (Abstracts) 2023: 71-72 - [c115]Jing Yu, Dimitar Ho, Adam Wierman:
Online Adversarial Stabilization of Unknown Networked Systems. SIGMETRICS (Abstracts) 2023: 73-74 - [c114]Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman:
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. SIGMETRICS (Abstracts) 2023: 83-84 - [c113]Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman:
Convergence rates for localized actor-critic in networked Markov potential games. UAI 2023: 2563-2573 - [i90]Yingying Li, James A. Preiss, Na Li, Yiheng Lin, Adam Wierman, Jeff S. Shamma:
Online switching control with stability and regret guarantees. CoRR abs/2301.08445 (2023) - [i89]Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman:
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. CoRR abs/2303.03100 (2023) - [i88]Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman:
Convergence Rates for Localized Actor-Critic in Networked Markov Potential Games. CoRR abs/2303.04865 (2023) - [i87]Xutong Liu, Jinhang Zuo, Siwei Wang, John C. S. Lui, Mohammad H. Hajiesmaili, Adam Wierman, Wei Chen:
Contextual Combinatorial Bandits with Probabilistically Triggered Arms. CoRR abs/2303.17110 (2023) - [i86]Adam Lechowicz, Nicolas Christianson, Jinhang Zuo, Noman Bashir, Mohammad H. Hajiesmaili, Adam Wierman, Prashant J. Shenoy:
The Online Pause and Resume Problem: Optimal Algorithms and An Application to Carbon-Aware Load Shifting. CoRR abs/2303.17551 (2023) - [i85]Jing Yu, Varun Gupta, Adam Wierman:
Online Stabilization of Unknown Linear Time-Varying Systems. CoRR abs/2304.02878 (2023) - [i84]Jinhang Zuo, Zhiyao Zhang, Zhiyong Wang, Shuai Li, Mohammad H. Hajiesmaili, Adam Wierman:
Adversarial Attacks on Online Learning to Rank with Click Feedback. CoRR abs/2305.17071 (2023) - [i83]Pengfei Li, Jianyi Yang, Adam Wierman, Shaolei Ren:
Learning-Augmented Decentralized Online Convex Optimization in Networks. CoRR abs/2306.10158 (2023) - [i82]Christopher Yeh, Jing Yu, Yuanyuan Shi, Adam Wierman:
Online learning for robust voltage control under uncertain grid topology. CoRR abs/2306.16674 (2023) - [i81]Pengfei Li, Jianyi Yang, Adam Wierman, Shaolei Ren:
Towards Environmentally Equitable AI via Geographical Load Balancing. CoRR abs/2307.05494 (2023) - [i80]Tongxin Li, Yiheng Lin, Shaolei Ren, Adam Wierman:
Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions. CoRR abs/2307.10524 (2023) - [i79]Yingying Li, Jing Yu, Lauren Conger, Adam Wierman:
Learning the Uncertainty Sets for Control Dynamics via Set Membership: A Non-Asymptotic Analysis. CoRR abs/2309.14648 (2023) - [i78]Bo Sun, Jerry Huang, Nicolas Christianson, Mohammad Hajiesmaili, Adam Wierman:
Online Algorithms with Uncertainty-Quantified Predictions. CoRR abs/2310.11558 (2023) - [i77]Pengfei Li, Jianyi Yang, Adam Wierman, Shaolei Ren:
Robust Learning for Smoothed Online Convex Optimization with Feedback Delay. CoRR abs/2310.20098 (2023) - [i76]Adam Lechowicz, Nicolas Christianson, Bo Sun, Noman Bashir, Mohammad Hajiesmaili, Adam Wierman, Prashant J. Shenoy:
Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms. CoRR abs/2310.20598 (2023) - [i75]Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman:
Best of Both Worlds: Stochastic and Adversarial Convex Function Chasing. CoRR abs/2311.00181 (2023) - [i74]Jianyi Yang, Pengfei Li, Tongxin Li, Adam Wierman, Shaolei Ren:
Anytime-Competitive Reinforcement Learning with Policy Prior. CoRR abs/2311.01568 (2023) - [i73]Jinhang Zuo, Zhiyao Zhang, Xuchuang Wang, Cheng Chen, Shuai Li, John C. S. Lui, Mohammad Hajiesmaili, Adam Wierman:
Adversarial Attacks on Cooperative Multi-agent Bandits. CoRR abs/2311.01698 (2023) - 2022
- [j99]John Z. F. Pang, Weixuan Lin, Hu Fu, Jack Kleeman, Eilyan Bitar, Adam Wierman:
Transparency and Control in Platforms for Networked Markets. Oper. Res. 70(3): 1665-1690 (2022) - [j98]Guannan Qu, Adam Wierman, Na Li:
Scalable Reinforcement Learning for Multiagent Networked Systems. Oper. Res. 70(6): 3601-3628 (2022) - [j97]Weici Pan, Guanya Shi, Yiheng Lin, Adam Wierman:
Online Optimization with Feedback Delay and Nonlinear Switching Cost. Proc. ACM Meas. Anal. Comput. Syst. 6(1): 17:1-17:34 (2022) - [j96]Tongxin Li, Ruixiao Yang, Guannan Qu, Guanya Shi, Chenkai Yu, Adam Wierman, Steven H. Low:
Robustness and Consistency in Linear Quadratic Control with Untrusted Predictions. Proc. ACM Meas. Anal. Comput. Syst. 6(1): 18:1-18:35 (2022) - [j95]Yu Su, Jannie Yu, Vivek Anand, Adam Wierman:
Learning-Augmented Energy-Aware Scheduling of Precedence-Constrained Tasks. SIGMETRICS Perform. Evaluation Rev. 49(2): 3-5 (2022) - [j94]Guocheng Liao, Yu Su, Juba Ziani, Adam Wierman, Jianwei Huang:
The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition. SIGMETRICS Perform. Evaluation Rev. 49(2): 6-8 (2022) - [c112]Yang Hu, Adam Wierman, Guannan Qu:
On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory (Extended Abstract). Allerton 2022: 1-2 - [c111]Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Competitive Control with Delayed Imperfect Information. ACC 2022: 2604-2610 - [c110]Yuanyuan Shi, Guannan Qu, Steven H. Low, Anima Anandkumar, Adam Wierman:
Stability Constrained Reinforcement Learning for Real-Time Voltage Control. ACC 2022: 2715-2721 - [c109]Chen Liang, Alessandro Zocca, Steven H. Low, Adam Wierman:
Interface Networks for Failure Localization in Power Systems. ACC 2022: 4540-4546 - [c108]Nicolas Christianson, Tinashe Handina, Adam Wierman:
Chasing Convex Bodies and Functions with Black-Box Advice. COLT 2022: 867-908 - [c107]Christopher Yeh, Jing Yu, Yuanyuan Shi, Adam Wierman:
Robust online voltage control with an unknown grid topology. e-Energy 2022: 240-250 - [c106]Yiheng Lin, Judy Gan, Guannan Qu, Yash Kanoria, Adam Wierman:
Decentralized Online Convex Optimization in Networked Systems. ICML 2022: 13356-13393 - [c105]Yang Hu, Adam Wierman, Guannan Qu:
On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory. NeurIPS 2022 - [c104]Yiheng Lin, Yang Hu, Guannan Qu, Tongxin Li, Adam Wierman:
Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity. NeurIPS 2022 - [c103]Weici Pan, Guanya Shi, Yiheng Lin, Adam Wierman:
Online Optimization with Feedback Delay and Nonlinear Switching Cost. SIGMETRICS (Abstracts) 2022: 81-82 - [c102]Tongxin Li, Ruixiao Yang, Guannan Qu, Guanya Shi, Chenkai Yu, Adam Wierman, Steven H. Low:
Robustness and Consistency in Linear Quadratic Control with Untrusted Predictions. SIGMETRICS (Abstracts) 2022: 107-108 - [i72]Daan Rutten, Nicolas Christianson, Debankur Mukherjee, Adam Wierman:
Online Optimization with Untrusted Predictions. CoRR abs/2202.03519 (2022) - [i71]Chenkai Yu, Hongyao Ma, Adam Wierman:
Price Cycles in Ridesharing Platforms. CoRR abs/2202.07086 (2022) - [i70]Yang Hu, Adam Wierman, Guannan Qu:
On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory. CoRR abs/2202.07187 (2022) - [i69]Jing Yu, Dimitar Ho, Adam Wierman:
Online Stabilization of Unknown Networked Systems with Communication Constraints. CoRR abs/2203.02630 (2022) - [i68]Yue Chen, Changhong Zhao, Steven H. Low, Adam Wierman:
An Energy Sharing Mechanism Considering Network Constraints and Market Power Limitation. CoRR abs/2203.04503 (2022) - [i67]Sungho Shin, Yiheng Lin, Guannan Qu, Adam Wierman, Mihai Anitescu:
Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems. CoRR abs/2204.05551 (2022) - [i66]Chen Liang, Alessandro Zocca, Steven H. Low, Adam Wierman:
Interface Networks for Failure Localization in Power Systems. CoRR abs/2205.06315 (2022) - [i65]Tongxin Li, Ruixiao Yang, Guannan Qu, Yiheng Lin, Steven H. Low, Adam Wierman:
Equipping Black-Box Policies with Model-Based Advice for Stable Nonlinear Control. CoRR abs/2206.01341 (2022) - [i64]Sahin Lale, Yuanyuan Shi, Guannan Qu, Kamyar Azizzadenesheli, Adam Wierman, Anima Anandkumar:
KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Dynamical Systems. CoRR abs/2206.01704 (2022) - [i63]Nicolas Christianson, Tinashe Handina, Adam Wierman:
Chasing Convex Bodies and Functions with Black-Box Advice. CoRR abs/2206.11780 (2022) - [i62]Christopher Yeh, Jing Yu, Yuanyuan Shi, Adam Wierman:
Robust Online Voltage Control with an Unknown Grid Topology. CoRR abs/2206.14369 (2022) - [i61]Jie Feng, Yuanyuan Shi, Guannan Qu, Steven H. Low, Anima Anandkumar, Adam Wierman:
Stability Constrained Reinforcement Learning for Real-Time Voltage Control in Distribution Systems. CoRR abs/2209.07669 (2022) - [i60]Bo Sun, Lin Yang, Mohammad H. Hajiesmaili, Adam Wierman, John C. S. Lui, Don Towsley, Danny H. K. Tsang:
The Online Knapsack Problem with Departures. CoRR abs/2209.11934 (2022) - [i59]Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman:
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. CoRR abs/2211.17116 (2022) - 2021
- [j93]Riley Murray, Venkat Chandrasekaran, Adam Wierman:
Newton Polytopes and Relative Entropy Optimization. Found. Comput. Math. 21(6): 1703-1737 (2021) - [j92]Riley Murray, Venkat Chandrasekaran, Adam Wierman:
Signomial and polynomial optimization via relative entropy and partial dualization. Math. Program. Comput. 13(2): 257-295 (2021) - [j91]Riley Murray, Venkat Chandrasekaran, Adam Wierman:
Publisher Correction to: Signomial and polynomial optimization via relative entropy and partial dualization. Math. Program. Comput. 13(2): 297-299 (2021) - [j90]Xingyu Zhou, Ness B. Shroff, Adam Wierman:
Asymptotically optimal load balancing in large-scale heterogeneous systems with multiple dispatchers. Perform. Evaluation 145: 102146 (2021) - [j89]Tongxin Li, Yue Chen, Bo Sun, Adam Wierman, Steven H. Low:
Information Aggregation for Constrained Online Control. Proc. ACM Meas. Anal. Comput. Syst. 5(2): 18:1-18:35 (2021) - [j88]Bo Sun, Lin Yang, Mohammad H. Hajiesmaili, Adam Wierman, John C. S. Lui, Don Towsley, Danny H. K. Tsang:
The Online Knapsack Problem with Departures. Proc. ACM Meas. Anal. Comput. Syst. 6(3): 57:1-57:32 (2021) - [j87]Mor Harchol-Balter, Takayuki Osogami, Alan Scheller-Wolf, Adam Wierman:
Correction to: Multi-server queueing systems with multiple priority classes. Queueing Syst. Theory Appl. 99(3-4): 397-398 (2021) - [j86]Tongxin Li, Bo Sun, Yue Chen, Zixin Ye, Steven H. Low, Adam Wierman:
Learning-Based Predictive Control via Real-Time Aggregate Flexibility. IEEE Trans. Smart Grid 12(6): 4897-4913 (2021) - [c101]Ali Zeynali, Bo Sun, Mohammad Hassan Hajiesmaili, Adam Wierman:
Data-driven Competitive Algorithms for Online Knapsack and Set Cover. AAAI 2021: 10833-10841 - [c100]Guannan Qu, Chenkai Yu, Steven H. Low, Adam Wierman:
Exploiting Linear Models for Model-Free Nonlinear Control: A Provably Convergent Policy Gradient Approach. CDC 2021: 6539-6546 - [c99]Noman Bashir, Tian Guo, Mohammad H. Hajiesmaili, David E. Irwin, Prashant J. Shenoy, Ramesh K. Sitaraman, Abel Souza, Adam Wierman:
Enabling Sustainable Clouds: The Case for Virtualizing the Energy System. SoCC 2021: 350-358 - [c98]Lucien Werner, Adam Wierman, Steven H. Low:
Pricing flexibility of shiftable demand in electricity markets. e-Energy 2021: 1-14 - [c97]Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman:
Stable Online Control of Linear Time-Varying Systems. L4DC 2021: 742-753 - [c96]Yiheng Lin, Yang Hu, Guanya Shi, Haoyuan Sun, Guannan Qu, Adam Wierman:
Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems. NeurIPS 2021: 5174-5185 - [c95]Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman:
Multi-Agent Reinforcement Learning in Stochastic Networked Systems. NeurIPS 2021: 7825-7837 - [c94]Bo Sun, Russell Lee, Mohammad H. Hajiesmaili, Adam Wierman, Danny H. K. Tsang:
Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems. NeurIPS 2021: 10339-10350 - [c93]Guocheng Liao, Yu Su, Juba Ziani, Adam Wierman, Jianwei Huang:
The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition. EC 2021: 689 - [c92]Tongxin Li, Yue Chen, Bo Sun, Adam Wierman, Steven H. Low:
Information Aggregation for Constrained Online Control. SIGMETRICS (Abstracts) 2021: 7-8 - [c91]Bo Sun, Ali Zeynali, Tongxin Li, Mohammad Hassan Hajiesmaili, Adam Wierman, Danny H. K. Tsang:
Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging. SIGMETRICS (Abstracts) 2021: 67-68 - [i58]Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman:
Stable Online Control of Linear Time-Varying Systems. CoRR abs/2104.14134 (2021) - [i57]Alessandro Zocca, Chen Liang, Linqi Guo, Steven H. Low, Adam Wierman:
A Spectral Representation of Power Systems with Applications to Adaptive Grid Partitioning and Cascading Failure Localization. CoRR abs/2105.05234 (2021) - [i56]Guocheng Liao, Yu Su, Juba Ziani, Adam Wierman, Jianwei Huang:
The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition. CoRR abs/2105.14262 (2021) - [i55]Shih-Hao Tseng, SooJean Han, Adam Wierman:
In-Network Freshness Control: Trading Throughput for Freshness. CoRR abs/2106.02156 (2021) - [i54]Noman Bashir, Tian Guo, Mohammad H. Hajiesmaili, David E. Irwin, Prashant J. Shenoy, Ramesh K. Sitaraman, Abel Souza, Adam Wierman:
Enabling Sustainable Clouds: The Case for Virtualizing the Energy System. CoRR abs/2106.08872 (2021) - [i53]Tongxin Li, Ruixiao Yang, Guannan Qu, Guanya Shi, Chenkai Yu, Adam Wierman, Steven H. Low:
Robustness and Consistency in Linear Quadratic Control with Predictions. CoRR abs/2106.09659 (2021) - [i52]Yiheng Lin, Yang Hu, Haoyuan Sun, Guanya Shi, Guannan Qu, Adam Wierman:
Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems. CoRR abs/2106.10497 (2021) - [i51]Bo Sun, Russell Lee, Mohammad H. Hajiesmaili, Adam Wierman, Danny H. K. Tsang:
Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems. CoRR abs/2109.01556 (2021) - [i50]Yuanyuan Shi, Guannan Qu, Steven H. Low, Anima Anandkumar, Adam Wierman:
Stability Constrained Reinforcement Learning for Real-Time Voltage Control. CoRR abs/2109.14854 (2021) - [i49]Weici Pan, Guanya Shi, Yiheng Lin, Adam Wierman:
Online Optimization with Feedback Delay and Nonlinear Switching Cost. CoRR abs/2111.00095 (2021) - 2020
- [j85]Desmond W. H. Cai, Anish Agarwal, Adam Wierman:
On the Inefficiency of Forward Markets in Leader-Follower Competition. Oper. Res. 68(1): 35-52 (2020) - [j84]Navid Azizan, Yu Su, Krishnamurthy Dvijotham, Adam Wierman:
Optimal Pricing in Markets with Nonconvex Costs. Oper. Res. 68(2): 480-496 (2020) - [j83]Zhixuan Fang, Longbo Huang, Adam Wierman:
Loyalty programs in the sharing economy: Optimality and competition. Perform. Evaluation 143: 102105 (2020) - [j82]Yang Cai, Federico Echenique, Hu Fu, Katrina Ligett, Adam Wierman, Juba Ziani:
Third-Party Data Providers Ruin Simple Mechanisms. Proc. ACM Meas. Anal. Comput. Syst. 4(1): 12:1-12:31 (2020) - [j81]Lin Yang, Mohammad Hassan Hajiesmaili, Ramesh K. Sitaraman, Adam Wierman, Enrique Mallada, Wing Shing Wong:
Online Linear Optimization with Inventory Management Constraints. Proc. ACM Meas. Anal. Comput. Syst. 4(1): 16:1-16:29 (2020) - [j80]Yiheng Lin, Gautam Goel, Adam Wierman:
Online Optimization with Predictions and Non-convex Losses. Proc. ACM Meas. Anal. Comput. Syst. 4(1): 18:1-18:32 (2020) - [j79]Ziv Scully, Lucas van Kreveld, Onno J. Boxma, Jan-Pieter L. Dorsman, Adam Wierman:
Characterizing Policies with Optimal Response Time Tails under Heavy-Tailed Job Sizes. Proc. ACM Meas. Anal. Comput. Syst. 4(2): 30:1-30:33 (2020) - [j78]Bo Sun, Ali Zeynali, Tongxin Li, Mohammad Hassan Hajiesmaili, Adam Wierman, Danny H. K. Tsang:
Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging. Proc. ACM Meas. Anal. Comput. Syst. 4(3): 51:1-51:32 (2020) - [j77]Xingyu Zhou, Ness B. Shroff, Adam Wierman:
Asymptotically Optimal Load Balancing in Large-scale Heterogeneous Systems with Multiple Dispatchers. SIGMETRICS Perform. Evaluation Rev. 48(3): 57-58 (2020) - [c90]Guannan Qu, Adam Wierman:
Finite-Time Analysis of Asynchronous Stochastic Approximation and $Q$-Learning. COLT 2020: 3185-3205 - [c89]Tongxin Li, Steven H. Low, Adam Wierman:
Real-time Flexibility Feedback for Closed-loop Aggregator and System Operator Coordination. e-Energy 2020: 279-292 - [c88]Guannan Qu, Adam Wierman, Na Li:
Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems. L4DC 2020: 256-266 - [c87]Guannan Qu, Yiheng Lin, Adam Wierman, Na Li:
Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward. NeurIPS 2020 - [c86]Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Online Optimization with Memory and Competitive Control. NeurIPS 2020 - [c85]Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman:
The Power of Predictions in Online Control. NeurIPS 2020 - [c84]Lin Yang, Mohammad Hassan Hajiesmaili, Ramesh K. Sitaraman, Adam Wierman, Enrique Mallada, Wing Shing Wong:
Online Linear Optimization with Inventory Management Constraints. SIGMETRICS (Abstracts) 2020: 7 - [c83]Yiheng Lin, Gautam Goel, Adam Wierman:
Online Optimization with Predictions and Non-convex Losses. SIGMETRICS (Abstracts) 2020: 9-10 - [c82]Ziv Scully, Lucas van Kreveld, Onno J. Boxma, Jan-Pieter L. Dorsman, Adam Wierman:
Characterizing Policies with Optimal Response Time Tails under Heavy-Tailed Job Sizes. SIGMETRICS (Abstracts) 2020: 35-36 - [c81]Palma London, Shai Vardi, Adam Wierman:
Logarithmic Communication for Distributed Optimization in Multi-Agent Systems. SIGMETRICS (Abstracts) 2020: 97-98 - [c80]Yang Cai, Federico Echenique, Hu Fu, Katrina Ligett, Adam Wierman, Juba Ziani:
Third-Party Data Providers Ruin Simple Mechanisms. SIGMETRICS (Abstracts) 2020: 103 - [c79]Chen Liang, Fengyu Zhou, Alessandro Zocca, Steven H. Low, Adam Wierman:
Mitigating Cascading Failures via Local Responses. SmartGridComm 2020: 1-7 - [i48]Guannan Qu, Adam Wierman:
Finite-Time Analysis of Asynchronous Stochastic Approximation and Q-Learning. CoRR abs/2002.00260 (2020) - [i47]Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Beyond No-Regret: Competitive Control via Online Optimization with Memory. CoRR abs/2002.05318 (2020) - [i46]