Below is a list of the papers (with PDFs provided, where available) that were invited or accepted for presentation at the 58th Annual Allerton Conference on Communication, Control, and Computing, which was held at the Allerton Park & Retreat Center, Monticello, Illinois, on September 28–30, 2022. As in past years, the Conference was sponsored by the Coordinated Science Laboratory and the Department of Electrical & Computer Engineering of the University of Illinois Urbana-Champaign. The Proceedings of the 58th Allerton Conference are available on IEEE Xplore.
- 2022 Proceedings foreword by conference chairs Alejandro Domínguez-García and Max Raginsky
- List of past Allerton Conference chairs
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Robustness of Gradient Methods for Data-Driven Decision Making
Mihailo Jovanovic (University of Southern California, USA)
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Wednesday, September 28
Session WeA1: Intersection of Learning, Optimization, & Control I
Organizer: Bin Hu.
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Convex Parameterization of Stabilizing Controllers and its LMI-based Computation via Filtering
Mauricio C. de Oliveira and Yang Zheng (University of California San Diego, USA)
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Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games
Thinh Doan (Virginia Tech, USA)
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TaSIL: Taylor Series Imitation Learning
Daniel Pfrommer (University of Pennsylvania, USA), Thomas Zhang (University of Pennsylvania, USA), Stephen Tu (Google, USA), and Nikolai Matni (University of Pennsylvania, USA)
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Optimal Private Data Acquisition: Central and Local Differential Privacy
Alireza Fallah (MIT, USA), Ali Makhdoumi (Duke University, USA), Azarakhsh Malekian (University of Toronto, USA), and Asu Ozdaglar (MIT, USA)
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Session WeA2: High Dimensional Statistics and Learning I
Organizers: Bruce Hajek, Jiaming Xu, Yihong Wu. Chair: Yuguo Chen (University of Illinois Urbana-Champaign, USA).
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Leave-one-out Singular Subspace Perturbation Analysis for Spectral Clustering
Anderson Ye Zhang (University of Pennsylvania, USA) and Harrison H. Zhou (Yale University, USA)
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Near-optimal Algorithms for Imitation Learning
Nived Rajaraman (University of California, Berkeley, USA), Yanjun Han (University of California, Berkeley, USA), Lin F. Yang (University of California, Los Angeles, USA), Kannan Ramchandran (University of California, Berkeley, USA), and Jiantao Jiao (University of California, Berkeley, USA)
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Selecting the Number of Communities in Count-Weighted Networks
Yucheng Liu and Xiaodong Li (UC Davis, USA)
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Session WeA3: Learning I
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Shachar Shayovitz and Meir Feder (Tel Aviv University, Israel)
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Jayanth Regatti, Hao Chen, and Abhishek Gupta (The Ohio State University, USA)
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Tomer Gafni (Ben-Gurion University of the Negev, Israel), Kobi Cohen (Ben-Gurion University of the Negev, Israel), and Yonina C. Eldar (Weizmann Institute of Science, Israel)
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Bryce L. Ferguson (University of California, Santa Barbara, USA), Daigo Shishika (George Mason University, USA), and Jason R. Marden (University of California, Santa Barbara, USA)
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Jialing Liao, Zheng Chen, and Erik G. Larsson (Linköping University, Sweden)
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Session WeA4: Information Theory and Coding I
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Shuche Wang (National University of Singapore, Singapore), Yuanyuan Tang (University of Virginia, USA), Ryan Gabrys (University of California San Diego, USA), and Farzad Farnoud (University of Virginia, USA)
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Krishna Gopal Benerjee and Adrish Banerjee (Indian Institute of Technology Kanpur, India)
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Zero-error Coding for Computing with Encoder Side-information
Nicolas Charpenay (IRISA, France), Maël Le Treust (ETIS UMR 8051, CY Université, ENSEA, CNRS, France), and Aline Roumy (INRIA, France)
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Keerthana Gurushankar (Carnegie Mellon University, USA), Praveen Venkatesh (Allen Institute, USA), and Pulkit Grover (Carnegie Mellon University, USA)
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Strategic Communication via Cascade Multiple-Description Network
Rony Bou Rouphael and Maël Le Treust (ETIS UMR 8051, ENSEA, CNRS, CY Cergy Paris Université, France)
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Session WeB1: Intersection of Learning, Optimization, and Control II
Organizer: Bin Hu.
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Momentum-Based Learning and Optimization Dynamics with Stochastic Restarting
Jorge I. Poveda (University of Colorado, Boulder, USA)
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Stability and Safety Constrained Reinforcement Learning for Voltage Control
Yuanyuan Shi (UCSD, USA)
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Representation-assisted Reinforcement Learning under Distribution Shift
Yuan Cheng (University of Science and Technology of China, China), Jing Yang (Pennsylvania State University, USA), and Yingbin Liang (The Ohio State University, USA)
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Mixed Strategies with Finite Support in Continuous Spaces: A Case Study in Trajectory Games
David Fridovich-Keil (University of Texas at Austin, USA)
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Session WeB2: Sequential Methods I
Organizers: G. Fellouris and V. Veeravalli.
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Quickest Detection of the Change of Community via Stochastic Block Models
Fei Sha (University of Nebraska-Lincoln, USA) and Ruizhi Zhang (University of Georgia, USA)
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Spatio-temporal Multiple Change-point Detection in Sensor Networks
Topi Halme (Aalto University, Finland), Eyal Nitzan (KIOXIA America, Israel), and Visa Koivunen (Aalto University, Finland)
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Tim Brucks (University of Texas at San Antonio, USA), Taposh Banerjee (University of Pittsburgh, USA), and Rahul Mishra (ISRO, India)
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Rui Zhang (Georgia Institute of Technology, USA), Yao Xie (Georgia Institute of Technology, USA), Rui Yao (Google, USA), and Feng Qiu (Argonne National Lab, USA)
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Window-Limited CUSUM for Sequential Change Detection
Liyan Xie (The Chinese University of Hong Kong, Shenzhen, China), George Moustakides (University of Patras, Greece), and Yao Xie (Georgia Institute of Technology, USA)
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Session WeB3: Networks, Learning, and Algorithms I
Organizers: Bruce Hajek and R. Srikant. Chair: Thinh Doan (Virginia Tech, USA).
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Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure
Hsu Kao (University of Michigan Ann Arbor, USA), Chen-Yu Wei (University of Southern California, USA), and Vijay Subramanian (University of Michigan, USA)
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Anand Kalvit and Assaf Zeevi (Columbia University, USA)
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A Survey of Dynamic Watermarking Algorithms and Some Recent Developments
Jiacheng Tang (GE Global Research, USA) and Abhishek Gupta (The Ohio State University, USA)
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Leveraging Spatial and Temporal Correlations in Distributed Learning
Divyansh Jhunjhunwala, Ankur Mallick, and Gauri Joshi (Carnegie Mellon University, USA)
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Session WeB4: Information Theory and Coding II
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Linghui Zhou, Tobias J. Oechtering, and Mikael Skoglund (KTH Royal Institute of Technology, Sweden)
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Junghoon Kim (Purdue University, USA), Seyyedali Hosseinalipour (Purdue University, USA), Taejoon Kim (University of Kansas, USA), David J. Love (Purdue University, USA), and Christopher G. Brinton (Purdue University, USA)
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Alejandro Lancho, Alexander Fengler, and Yury Polyanskiy (Massachusetts Institute of Technology, USA)
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Francisco Pernice (Stanford University, USA)
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Session WeC1: Networks, Learning, and Algorithms II
Organizers: Bruce Hajek and R. Srikant. Chair: Assaf Zeevi (Columbia University, USA).
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Beyond No Regret: Instance-Dependent PAC Reinforcement Learning
Andrew Wagenmaker (University of Washington, USA), Max Simchowitz (UC Berkeley, USA), and Kevin Jamieson (University of Washington, USA)
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Michael J. Neely (University of Southern California, USA)
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The Multisecretary Problem: Regret, Approximation and Learning
Siddhartha Banerjee (Cornell University, USA)
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Markovian Interference in Experiments
Vivek Farias (MIT, USA)
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Session WeC2: Sequential Methods II
Organizers: G. Fellouris and V. Veeravalli.
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Efficient SPRT-based Best Arm Identification in Stochastic Bandits
Arpan Mukherjee and Ali Tajer (RPI, USA)
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Yuyang Shi and Yajun Mei (Georgia Institute of Technology, USA)
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Data-Driven Sequential Change Detection in Privacy-Sensitive Networks
Mehmet Necip Kurt (Columbia University, USA), Yasin Yilmaz (University of South Florida, USA),Xiaodong Wang (Columbia University, USA), and Pieter J. Mosterman (MathWorks, USA)
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Hadar Szostak and Kobi Cohen (Ben-Gurion University Of The Negev, Israel)
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Session WeC3: Representation, Learning, and Inference
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Pradeep Kr. Banerjee (Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany), Kedar Karhadkar (UCLA, USA), Yu Guang Wang (Shanghai Jiao Tong University, China), Uri Alon (CMU, USA), and Guido Montúfar (UCLA and MPI MiS, USA)
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Ben A. Kizaric and Daniel L. Pimentel-Alarcón (University of Wisconsin-Madison, USA)
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Xiangxiang Xu and Lizhong Zheng (MIT, USA)
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Xinyi Tong (Tsinghua University, China), Xiangxiang Xu (MIT, USA), and Shao-Lun Huang (Tsinghua-Berkeley Shenzhen Institute, China)
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Diego R. Benalcazar and Chinwendu Enyioha (University of Central Florida, USA)
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Session WeC4: Learning II
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Yigit E. Bayiz and Ufuk Topcu (University of Texas at Austin, USA)
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Yili Zhang, Asaf Cohen, and Vijay G. Subramanian (University of Michigan, USA)
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Sajjad Bahrami and Ertem Tuncel (University of California, Riverside, USA)
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Yulan Zhang (Yale University, USA), Anna C. Gilbert (Yale University, USA), and Stefan Steinerberger (University of Washington, USA)
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Ivan Perez Avellaneda and Luis A. Duffaut Espinosa (University of Vermont, USA)
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Session WeD1: Networks, Learning, and Algorithms III
Organizers: Bruce Hajek and R. Srikant. Chair: Richard Sowers (University of Illinois Urbana-Champaign, USA).
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Rohan Deb, Meet Gandhi, and Shalabh Bhatnagar (Indian Institute of Science, India)
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Harsh Dolhare and Vivek Borkar (Indian Institute of Technology Bombay, India)
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Global Convergence of Federated Learning for Mixed Regression
Lili Su (Northeastern University, USA), Jiaming Xu (Duke University, USA), and Pengkun Yang (Tsinghua University, China)
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Zixian Yang (University of Michigan, Ann Arbor, USA), Xin Liu (ShanghaiTech University, China), and Lei Ying (The University of Michigan, Ann Arbor, USA)
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On Representation Learning with Model-Agnostic Meta-Learning
Liam Collins (The University of Texas at Austin, USA), Aryan Mokhtari (The University of Texas at Austin, USA), Sewoong Oh (University of Washington at Seattle, USA), and Sanjay Shakkottai (The University of Texas at Austin, USA)
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Session WeD2: Robust Inference and Learning
Organizer: V. Veeravalli.
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A Distributionally Robust Approach to Domain Adaptation
Akram Awad and George Atia (University of Central Florida, USA)
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Policy Gradient Method For Robust Reinforcement Learning
Yue Wang and Shaofeng Zou (University at Buffalo, the State University of New York, USA)
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Post-hoc Uncertainty Learning using a Dirichlet Meta-Model
Maohao Shen (MIT, USA), Yuheng Bu (MIT, USA), Prasanna Sattigeri (IBM Research, USA), Soumya Ghosh (IBM Research, USA), Subhro Das (IBM Research, USA), and Gregory Wornell (MIT, USA)
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Vikram Krishnamurthy (Cornell University, USA) and Luke Snow (Cornell University, USA)
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Xinyi Ni and Lifeng Lai (University of California, Davis, USA)
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Session WeD3: Estimation, Prediction, and Control
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Yunhan Huang, Tao Zhang, and Quanyan Zhu (New York University, USA)
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Po-Han Li, Ufuk Topcu, and Sandeep P. Chinchali (The University of Texas at Austin, USA)
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W. Steven Gray (Old Dominion University, USA)
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Pouria Tooranjipour, Bahare Kiumarsi, and Hamidreza Modares (Michigan State University, East Lansing, USA)
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Beyond UCB: Statistical Complexity and Optimal Algorithm for Non-linear Ridge Bandits
Yanjun Han (Massachusetts Institute of Technology, USA), Jiantao Jiao (University of California, Berkeley, USA), Nived Rajaraman (University of California, Berkeley, USA), and Kannan Ramchandran (University of California, Berkeley, USA)
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Session WeD4: Queueing Systems
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Xinyu Wu, Dan Wu, and Eytan Modiano (Massachusetts Institute of Technology, USA)
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Adrian Redder (Paderborn University, Germany), Arunselvan Ramaswamy (Karlstad University, Sweden), and Holger Karl (Hasso-Plattner-Institute, Potsdam University, Germany)
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Purbesh Mitra and Sennur Ulukus (University of Maryland, USA)
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Bai Liu and Eytan Modiano (Massachusetts Institute of Technology, USA)
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Tushar Shankar Walunj, Shiksha Singhal, Veeraruna Kavitha, and Jayakrishnan Nair (IIT Bombay, India)
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Thursday, September 29
Session ThA1: Games and Distributed Optimization/Learning I
Organizers: Rasoul Etesami and Tamer Başar.
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On the Connection between Reinforcement Learning and Gradient Descent
Alex Olshevsky (Boston University, USA)
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Xiaochun Niu and Ermin Wei (Northwestern University, USA)
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Random Adaptation Perspective to Distributed Computation
Behrouz Touri, Rohit Parasnis, Massimo Franceschetti, and Ashwin Verma (University of California San Diego, USA)
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Yang Hu (Harvard University, USA), Adam Wierman (Caltech, USA), and Guannan Qu (Carnegie Mellon University, USA)
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Session ThA2: Electric Power Systems I
Organizers: A. Domínguez-García and S. Bose. Chair: Subhonmesh Bose (University of Illinois Urbana-Champaign, USA).
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Convex Optimization of Bioprocesses
Josh Taylor (University of Toronto, Canada)
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A Safe Pricing Algorithm for Distributed Demand Management
Mahnoosh Alizadeh (University of California Santa Barbara, USA)
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Cong Chen and Lang Tong (Cornell University, USA)
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Inverse Power Flow Problem
Ye Yuan (Huazhong University of Science and Technology, China), Steven Low (Caltech, USA), Omid Ardakanian (University of Alberta, Canada), and Claire Tomlin (UC Berkeley, USA)
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Nicolaos E. Manitara, Christoforos N. Hadjicostis, and Themistoklis Charalambous (University of Cyprus, Cyprus)
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Session ThA3: Intersection of Learning, Optimization, and Control III
Organizer: Bin Hu.
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Mohammad Taha Toghani and César A. Uribe (Rice University, USA)
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Escaping Saddle Points in Zeroth-order Optimization: Two Function Evaluations Suffice
Zhaolin Ren and Na Li (Harvard University, USA)
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Symmetric Natural Policy Gradient for Regularized Multi-Agent Learning with Parameter Convergence
Sarath Pattathil, Kaiqing Zhang, and Asu Ozdaglar (MIT, USA)
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Black-box Control for Linear Dynamical Systems
Xinyi Chen and Elad Hazan (Princeton University and Google AI Princeton, USA)
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Session ThA4: High-Dimensional Statistics and Learning II
Organizers: Bruce Hajek, Jiaming Xu, and Yihong Wu. Chair: Feng Liang (University of Illinois Urbana-Champaign, USA).
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On the Sample Complexity of Entropic Optimal Transport
Philippe Rigollet and Austin Stromme (Massachusetts Institute of Technology, USA)
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Detection-Recovery Gap for Planted Dense Cycles
Cheng Mao (Georgia Institute of Technology, USA) and Alexander Wein (University of California, Davis, USA)
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Recursive Causal Structure Learning
Negar Kiyavash (EPFL, Switzerland), Sina Akbari (EPFL, Switzerland), Ehsan Mokhtarian (EPFL, Switzerland), and Amiremad Ghassami (JHU, USA)
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The TAP Free Energy for High-dimensional Linear Regression with Uniform Spherical Prior
Jiaze Qiu and Subhabrata Sen (Harvard University, USA)
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Local Convexity of the TAP Free Energy and AMP Convergence for Z2-synchronization
Song Mei (UC Berkeley, USA), Michael Celentano (UC Berkeley, USA), and Zhou Fan (Yale University, USA)
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Session ThPL: Todd Coleman Plenary Lecture
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Systems- and Information-Theoretic Approaches to Decipher Oscillations in Neural Systems (abstract)
Todd Coleman (Stanford University, USA)
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Session ThC1: High-Dimensional Statistics and Learning III
Organizers: Bruce Hajek, Jiaming Xu, and Yihong Wu. Chair: Jiaming Xu (Duke University, USA).
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Phase Transitions in the Gaussian Database Alignment and Planted Gaussian Matching Problems
Daniel Cullina (Penn State, USA)
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Low-rank Matrix Estimation with Groupwise Heteroskedasticity
Galen Reeves (Duke University, USA)
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Peizhong Ju (The Ohio State University, USA), Xiaojun Lin (Purdue University, USA), and Ness B. Shroff (The Ohio State University, USA)
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Universality of High-Dimensional Estimation with Nearly Deterministic Sensing Matrices
Rishabh Dudeja, Subhabrata Sen, and Yue Lu (Harvard University, USA)
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Session ThC2: Electric Power Systems II
Organizers: A. Domínguez-García and S. Bose.
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Stable and Decentralized Learning for Voltage Regulation
Wenqi Cui (University of Washington, USA), Weiwei Yang (Microsoft, USA), and Baosen Zhang (University of Washington, USA)
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Bernard C. Lesieutre (University of Wisconsin-Madison, USA), Yasmine Abdennadher (University of Wisconsin-Madison, USA), and Sandip Roy (Washington State University, USA)
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Tong Wu (Cornell University, USA), Anna Scaglione (Cornell University, USA), and Daniel Arnold (Lawrence Berkeley National Lab, USA)
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Bringing Data Science and Machine Learning into Electricity Markets
Yury Dvorkin (Johns Hopkins University, USA)
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Sunho Jang, Necmiye Ozay, and Johanna L. Mathieu (University of Michigan, USA)
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Session ThC3: Games and Networks
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Philip N. Brown, Brandon Collins, Colton Hill, Gia Barboza, and Lisa Hines (UCCS, USA)
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Xing Gao and Lev Reyzin (University of Illinois at Chicago, USA)
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Carmel Fiscko (Carnegie Mellon University, USA), Soummya Kar (Carnegie Mellon University, USA), and Bruno Sinopoli (Washington University in St. Louis, USA)
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Adel Aghajan, Keith Paarporn, and Jason R. Marden (University of California Santa Barbara, USA)
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Jean-Baptiste Seby, Charles Harvey, and Saurabh Amin (Massachusetts Institute of Technology, USA)
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Session ThC4: Control and Algorithms I
Organizer: Daniel Liberzon.
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Second Order Methods for Min-Max Optimization with Stability Guarantees
Raphael Chincilla, Guosong Yang, and Joao Hespanha (University of California, Santa Barbara, USA)
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Teng Guo, Si Wei Feng, Mario Szegedy, and Jingjin Yu (Rutgers University, USA)
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Guaranteeing Safety for Systems with Missing Measurements
Necmiye Ozay (University of Michigan, USA) and Liren Yang (Huazhong University of Science and Technology, China)
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Asymptotically Optimal Worst-Case State Estimation over Noisy Channels
Ghassen Zafzouf, Farhad Farokhi, and Girish Nair (University of Melbourne, Australia)
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Randy A. Freeman (Northwestern University, USA)
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Session ThD1: Electric Power Systems III
Organizers: A. Domínguez-García and S. Bose.
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Manish K. Singh, D. Venkatramanan, and Sairaj Dhople (University of Minnesota, USA)
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Dominic Groß (University of Wisconsin-Madison, USA)
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From Automatic Generation Control to Fast Frequency Control using Inverter-Based Resources
John Simpson-Porco (University of Toronto, Canada)
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Sijia Geng (Johns Hopkins University, USA) and Ian Hiskens (University of Michigan, USA)
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Approaches to Analysis of Power System Dynamics with High Penetration of Inverter Interfaced Devices
Kevin Tomsovic, Fatima Taousser, and Seddik Djouadi (University of Tennessee, USA)
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Session ThD2: Games and Distributed Optimization/Learning II
Organizers: Rasoul Etesami and Tamer Başar.
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Information Provision to Manage Strategic Agents over Star Networks: Static and Dynamic Designs
Sohil Shah, Saurabh Amin, and Patrick Jaillet (Massachusetts Institute of Technology, USA)
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Gradient Play in Stochastic Games: Stationary Points, Convergence, and Sample Complexity
Runyu Zhang, Zhaolin Ren, and Na Li (Harvard University, USA)
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Persuasion in Networks: Public Signals and Cores
Ozan Candogan (University of Chicago, Booth School of Business, USA)
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The Art of Concession in General Lotto Games
Jason Marden (University of California, Santa Barbara, USA), Rahul Chandan (University of California, Santa Barbara, USA), Keith Paarporn (University of California, Santa Barbara, USA), Mahnoosh Alizadeh (University of California, Santa Barbara, USA), and Dan Kovenock (Chapman University, USA)
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Session ThD3: Information Theory and Statistical Inference
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Huanran Li and Daniel Pimentel-Alarcón (University of Wisconsin-Madison, USA)
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Meng-Che Chang, Shi-Yuan Wang, and Matthieu R. Bloch (Georgia Institute of Technology, USA)
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Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, and Mikael Skoglund (KTH, Sweden)
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Adam Case (Drake University, USA) and Jack H. Lutz (Iowa State University, USA)
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Mano Vikash Janardhanan (Balyasny Asset Management, USA) and Lev Reyzin (University of Illinois at Chicago, USA)
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Session ThD4: Theoretical Understandings of Machine Learning
Organizers: Yue M. Lu and Minh N. Do.
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Overparameterization Improves Robustness to Covariate Shift in High Dimensions
Nilesh Tripuraneni (U.C. Berkeley, USA), Ben Adlam (Google Brain, USA), and Jeffrey Pennington (Google Brain, USA)
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Abdulkadir Canatar and Cengiz Pehlevan (Harvard University, USA)
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Session ThD5: Control and Algorithms II
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A. Mulgund, R. Shekhar, N. Devroye, Gy. Turán, and M. Žefran (University of Illinois Chicago, USA)
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On the Conley’s Decomposition for Well-posed Hybrid Inclusions
Rafal Goebel (Loyola University of Chicago, USA)
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Friday, September 30
Session FrA1: Networks, Learning, and Algorithms IV
Organizers: Bruce Hajek and R. Srikant. Chair: Sasha Stolyar (University of Illinois Urbana-Champaign, USA).
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Optimal Scheduling for Multi-Server Systems: Adversarial versus Stochastic Viewpoints
Mor Harchol-Balter, Isaac Grosof, and Ziv Scully (Carnegie Mellon University, USA)
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Maximizing Utilization in Large Systems Serving Jobs with Time-Varying Resource Requirements
Yige Hong (Carnegie Mellon, USA), Qiaomin Xie (University of Wisconsin-Madison, USA), and Weina Wang (Carnegie Mellon University, USA)
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Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning
Young Wu, Jeremy McMahan, Jerry Zhu, Qiaomin Xie (University of Wisconsin-Madison, USA)
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Is Pessimism Provably Efficient for Offline RL?
Zhaoran Wang (Northwestern University, USA)
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Simina Brânzei (Purdue University, USA), Erel Segal-Halevi (Ariel University, Israel), and Aviv Zohar (Hebrew University of Jerusalem, Israel)
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Session FrA2: Multiuser Channels and Networks
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Paul Sheldon, Besma Smida, Natasha Devroye, and Daniela Tuninetti (University of Illinois Chicago, USA)
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Rémi Chou (Wichita State University, USA) and Matthieu R. Bloch (Georgia Tech, USA)
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Abhinanda Dutta and Steven Weber (Drexel University, USA)
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Jonathan Ponniah (San Jose State University, USA)
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Ningze Wang, Anoosheh Heidarzadeh, and Alex Sprintson (Texas A&M University, USA)
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Session FrA3: Imaging and Data Science
Organizers: Zhizhen Zhao, Ivan Dokmanic, and Minh Do.
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Diyu Yang (Purdue University, USA), Craig A. J. Kemp (Eli Lilly and Company, USA), Gregery T. Buzzard (Purdue University, USA), and Charles A. Bouman (Purdue University, USA)
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A Geometric Analysis of Neural Collapse with Unconstrained Features
Qing Qu (University of Michigan, USA)
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Robust Deep Image Prior with Partial Guidance
Shijun Liang (Michigan State University, USA), Xiang Li (University of Michigan, USA), Avrajit Ghosh (Michigan State University, USA), Qing Qu (University of Michigan, USA), and Saiprasad Ravishankar (Michigan State University, USA)
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A Regularized Conditional GAN for Posterior Sampling in Inverse Problems
Matt Bendel, Rizwan Ahmad, and Philip Schniter (Ohio State, USA)
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Session FrB1: Networks, Learning, and Algorithms V
Organizers: Bruce Hajek and R. Srikant. Chair: Vijay Subramanian (University of Michigan, USA).
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Caio Kalil Lauand and Sean Meyn (University of Florida, USA)
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Nathan Dahlin (UIUC, USA), Kevin Chang (University of Southern California, USA), Krishna Chaitanya Kalagarla (USC, USA), Rahul Jain (University of Southern California, USA), and Pierluigi Nuzzo (USC, USA)
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Gokcan Tatli, Rob Nowak, and Ramya Korlakai Vinayak (University of Wisconsin-Madison, USA)
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Ignoring Causality to Improve Ranking
Shuo Yang and Sujay Sanghavi (UT Austin, USA)
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Session FrB2: Topics in Optimization
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Itamar Katz and Yuval Kochman (Hebrew University of Jerusalem, Israel)
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Mustafa O. Karabag, David Fridovich-Keil, and Ufuk Topcu (The University of Texas at Austin, USA)
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Iyanuoluwa Emiola and Chinwendu Enyioha (University of Central Florida, USA)
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Zhanhong Jiang (Johnson Controls, USA), Aditya Balu (Iowa State University, USA), Xian Yeow Lee (Iowa State University, USA), Young M. Lee (Johnson Controls, USA), Chinmay Hegde (New York University, USA), and Soumik Sarkar (Iowa State University, USA)
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Lihui Yi and Ermin Wei (Northwestern University, USA)
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Session FrB3: Coding Techniques
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Cornelia Ott (Ulm University, Germany), Hedongliang Liu (Technical University of Munich, Germany), and Antonia Wachter-Zeh (Technical University of Munich, Germany)
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Dror Chawin and Ishay Haviv (The Academic College of Tel Aviv-Yaffo, Israel)
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Fatemeh Kazemi (Texas A&M University, USA), Ningze Wang (Texas A&M University, USA), Rafael G. L. D’Oliveira (Clemson University, USA), and Alex Sprintson (Texas A&M University, USA)
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Neophytos Charalambides (University of Michigan, USA), Mert Pilanci (Stanford University, USA), and Alfred O. Hero III (University of Michigan, USA)
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Josiah Park, Carlos Saltijeral, and Ming Zhong (Texas A&M University, USA)
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Kenneth Palacio-Baus (Universidad de Cuenca, Ecuador) and Natasha Devroye (University of Illinois Chicago, USA)
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