ALLERTON 2023: 2023 ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, & COMPUTING

A
Abbasi, Ahmed Ali	AltGDMin for Fast Federated Low Rank Matrix Completion
Abedinzadeh, Mohammadhossein	A Multidimensional Opinion Evolution Model with Confirmation Bias
Adikari, Tharindu	Straggler Exploitation in Distributed Computing Systems with Task Grouping
Agrawal, Ishank	Feature Geometry of Multivariate Dependence and Applications
Agrawal, Shubhada	Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise
Akyol, Emrah	A Multidimensional Opinion Evolution Model with Confirmation Bias Strategic Quantization of a Noisy Source
Al Taha, Feras	Learning in Network Games with Dynamic Populations
Al-Lawati, Haider	Straggler Exploitation in Distributed Computing Systems with Task Grouping
Alahmed, Ahmed	Operating-Envelopes-Aware Decentralized Welfare Maximization for Energy Communities
Alam, Syed Eqbal	Communication-efficient Federated Multi-resource Allocation: A Non-homogeneous Markov Chain Model Near Optimal Differentially Private Client Selection in Federated Settings
Alghamdi, Wael	The Saddle-Point Method in Differential Privacy
Alur, Rajeev	Stability Guarantees for Feature Attributions with Multiplicative Smoothing
Anand, Anju	Strategic Quantization of a Noisy Source
Anderson, Lindsay	Aggregating Power Networks for Decentralized Control: A Spectral Clustering Approach
Arefizadeh, Sina	Characterization of Potential Games: Application in Aggregative Games
Arslantas, Yuksel	Convergence of Heterogeneous Learning Dynamics in Zero-sum Stochastic Games
Asoodeh, Shahab	The Saddle-Point Method in Differential Privacy
Atia, George	Robust Average-Reward Markov Decision Processes
Avella, Marco	Asymptotics for alpha-posteriors with applications to variational inference
B
Babu, Silpa	A Fast Algorithm for Low Rank + Sparse column-wise Compressive Sensing
Balzano, Laura	Manifold Optimization for Data Driven Reduced-Order Modeling
Banerjee, Siddhartha	Priorities and Quotas in Online Matching
Banerjee, Taposh	Score-Based Bayesian Quickest Change Detection
Ben Yacoub, Emna	Trapping and Absorbing Set Enumerators for Multi-Edge Type LDPC Code Ensembles
Bernstein, Andrey	Operating-Envelopes-Aware Decentralized Welfare Maximization for Energy Communities
Berry, Randall	Bayesian Observational Learning in Mean-Field Games with Imperfect Observations Incentive Mechanism Design for Federated Learning and Unlearning
Borkar, Vivek	Online Parameter Estimation in Partially Observed Markov Decision Processes
Bouman, Charles	Generative Plug and Play: Posterior Sampling for Inverse Problems
Brinton, Christopher	Derandomizing Codes for the Binary Adversarial Wiretap Channel of Type II Preserving Sparsity and Privacy in Straggler-Resilient Distributed Matrix Computations
Brânzei, Simina	Phase Transitions for Diversity in Stochastic Block Model Dynamics
Bu, Yuheng	Group Fairness with Uncertainty in Sensitive Attributes
Busic, Ana	Inverse-Free Zap Stochastic Approximation
Buzzard, Gregery	Generative Plug and Play: Posterior Sampling for Inverse Problems
C
Calmon, Flavio	The Saddle-Point Method in Differential Privacy
Candogan, Ozan	Information Design for Spatial Resource Allocation
Cao, Shuchen	An Adaptive Approach for Online Monitoring of Large Scale Data Streams
Caramanis, Constantine	Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD
Cavraro, Guido	Operating-Envelopes-Aware Decentralized Welfare Maximization for Energy Communities
Chakraborty, Kaustav	Discovering and Learning from Closed-Loop Failures of Vision-based Controllers.
Chakraborty, Sayantan	One-Shot Non-Catalytic Distributed Purity Distillation
Chandrasekaran, Venkat	Any-dimensional convex sets
Chen, Wei-Ning	Training generative models from privatized data
Chen, Xin	Verification and Design of Robust and Safe Neural Network-enabled Autonomous Systems
Chen, Xudong	Super-linearization of Polynomial Systems
Chen, Yudong	Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption
Chen, Yudong	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Cheng, Hao-Chung	Privacy Amplification Against Quantum Side Information Via Regular Random Binning
Cheng, Kuan	On $k$-Mer-Based and Maximum Likelihood Estimation Algorithms for Trace Reconstruction
Chi, Yuejie	The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
Chiu, Chih-Yuan	Dynamic Tolling in Arc-based Traffic Assignment Models
Cho, Young-ho	Topology-aware Piecewise Linearization of the AC Power Flow through Generative Modeling
Chou, Remi	Distributed Storage Over a Public Channel: Trade-off between Privacy and Shared Key Lengths
Chung, Hye Won	Graph Matching in Correlated Stochastic Block Models for Improved Graph Clustering
Collins, Liam	On representation learning with the InfoNCE loss
Combes, Richard	Curse of Dimension of Thompson Sampling for Combinatorial Bandits
Coogan, Samuel	Interaction-aware interval reachability of neural network controlled systems
Cotardo, Giuseppe	Multishot Adversarial Network Decoding
Cui, Wenqi	Leveraging Predictions in Power System Frequency Control: an Adaptive Approach
Cullina, Daniel	Characterizing optimal loss for adversarial classification versus multiple adversaries
Cutler, Joshua	Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality
D
Das, Anindya Bijoy	Preserving Sparsity and Privacy in Straggler-Resilient Distributed Matrix Computations
Das, Rudrajit	Understanding Self Distillation
Das, Subhro	Group Fairness with Uncertainty in Sensitive Attributes
Dau Son, Hoang	New results on Erasure Combinatorial Batch Codes
Deshmukh, Jyotirmoy V.	Conformal Prediction for STL Runtime Verification
Deylam Salehi, Mohammad Reza	An Achievable Low Complexity Encoding Scheme for Coloring Cyclic Graphs
Diaz, Mateo	Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality
Ding, Jie	Exploring Gradient Oscillation in Deep Neural Network Training
Ding, Ningning	Incentive Mechanism Design for Federated Learning and Unlearning
Doan, Thinh	A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning
Dong, Shi	Fine-Tuning Language Models with Advantage-Induced Policy Alignment
Draper, Stark	Straggler Exploitation in Distributed Computing Systems with Task Grouping
Drusvyatskiy, Dmitriy	Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality
Du, Zhe	Manifold Optimization for Data Driven Reduced-Order Modeling
Duffaut Espinosa, Luis	Backward and Inner Approximation of Output Reachable sets via Chen-Fliess Series
Dwivedi, Raaz	On counterfactual inference with unobserved confounding
E
Ebenezer, William	Adaptive Identification from a Support Vector Perspective
Ebrahimi, Raman	United We Fall: On the Nash Equilibria of Multiplex Network Games
Eghbal, Sina	An Improved Greedy Cover Algorithm for Pliable Index Coding
Eichhorn, Matthew	Priorities and Quotas in Online Matching
El Alaoui, Ahmed	Stochastic localization and algorithmic variants
Entesari, Taha	Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Erkip, Elza	Single-Shot Lossy Compression for Joint Inference and Reconstruction
Esmaeilbeig, Zahra	Deep Learning Meets Adaptive Filtering: A Stein's Unbiased Risk Estimator Approach
Everett, Michael	Backward Reachability Analysis for Safety Verification of Neural Feedback Loops
F
Fan, Chuchu	Neural Network-based Fault Detection and Identification for Quadrotors using Dynamic Symmetry
Farahvash, Faraz	Delay Performance Optimization with Packet Drop Stochastic Control under Correlated Disturbances
Farnoud, Farzad	Active Ranking without Strong Stochastic Transitivity
Farrell, Xavier	Quantifying Confidence in Electricity Rate Plan Recommendations Considering Variability in Future Electricity Usage
Fattahi, Salar	Blessing of Nonconvexity in Factorized Models
Faw, Matthew	Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD
Fazlyab, Mahyar	Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Fekri, Faramarz	A Density Evolution Framework for Recovery of Covariance and Causal Graphs from Compressed Measurements
Ferguson, Bryce	Communication Enabled Collaborations in Multi-Agent Systems
Ferragut, Andres	Dynamic Load Balancing of Selfish Drivers between Spatially Distributed Electrical Vehicle Charging Stations
Fonseca Jr, Benedito	Fairness in Distributed Sensor Systems to Detect Emitters
Freund, Daniel	Quantifying the Cost of Learning in Queueing Systems
Frujeri, Felipe	Fine-Tuning Language Models with Advantage-Induced Policy Alignment
Fu, Feisi	Verification and Design of Robust and Safe Neural Network-enabled Autonomous Systems
G
Gabrys, Ryan	Cover Your Bases: How to Minimize the Sequencing Coverage in DNA Storage Systems
Gallego-Posada, Jose	Explorations on scalable preconditioned gradient methods for deep learning
Gao, Jie	Sequential Change-Point Detection for Correlation Matrices
Gao, Li	Privacy Amplification Against Quantum Side Information Via Regular Random Binning
Gao, Sicun	Towards Rigorous Use of Neural Networks in Nonlinear Control
Gao, Xing	A Unified Analysis of Dynamic Interactive Learning
Garcia-Frias, Javier	Non-Linear Analog Coding for Image Transmission over Noisy Channels
Garg, Kunal	Neural Network-based Fault Detection and Identification for Quadrotors using Dynamic Symmetry
Gaudio, Julia	"All-Something-Nothing" Phase Transitions in Planted Subgraph Recovery
Gerber, Patrik	Likelihood-free hypothesis testing
Geshkovski, Borjan	Clustering in transformers: an interacting particle systems perspective
Ghasemi, Mahsa	Inverse Reinforcement Learning with Learning and Leveraging Demonstrators' Varying Expertise Levels
Giannou, Angeliki	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Gimpel, Andreas	Embracing errors is more effective than avoiding them through constrained coding for DNA data storage
Gomez, Juan Felipe	The Saddle-Point Method in Differential Privacy
Graifer, Michael	Quantum Key Distribution with State Replacement
Grass, Robert N.	Embracing errors is more effective than avoiding them through constrained coding for DNA data storage
Gray, W. Steven	Linear Operator Differential Equations with Applications to Linear Time-Varying Systems
Grigorescu, Elena	On $k$-Mer-Based and Maximum Likelihood Estimation Algorithms for Trace Reconstruction
Gross, Dominic	Towards constrained grid-forming control
Gu, Quanquan	Active Ranking without Strong Stochastic Transitivity
Guo, Dongning	Distributed MARL for Scheduling in Conflict Graphs
Guruswamy Sethuraman, Muralikrishnna	A Density Evolution Framework for Recovery of Covariance and Causal Graphs from Compressed Measurements
H
Haddock, Jamie	On Subsampled Quantile Randomized Kaczmarz
Hadjicostis, Christoforos	Privacy-Preserving Distributed k-means Clustering with Quantized Communication in Finite Time
Hajar, Joudi	Wasserstein Distributionally Robust Regret-Optimal Control under Partial Observability
Han, Barron	Coded Kalman Filtering Over Gaussian Channels with Feedback
Han, Yuming	On Energy-Delay Tradeoff in Uncoordinated MAC
Han, Yuze	Complete Asymptotic Analysis for Projected Stochastic Approximation and Debiased Variants
Harapanahalli, Akash	Interaction-aware interval reachability of neural network controlled systems
Hashemi, Abolfazl	Relative Entropy Regularization for Robust Submodular Multi-Task Subset Selection High Probability Guarantees For Federated Learning.
Hashemi, Morteza	An Efficient Distributed Multi-Agent Reinforcement Learning for EV Charging Network Control
Hassibi, Babak	Wasserstein Distributionally Robust Regret-Optimal Control under Partial Observability
Hassibi, Babak	Coded Kalman Filtering Over Gaussian Channels with Feedback
He, Wenbo	A Differential Dynamic Programming-based Approach for Balancing Energy and Time Optimality in Motion Planning
Heckel, Reinhard	Embracing errors is more effective than avoiding them through constrained coding for DNA data storage
Heidaribeni, Nasimeh	A variational approach to federated and robust learning
Hindupur, Sai Sumedh	Online Parameter Estimation in Partially Observed Markov Decision Processes
Hong, Yige	Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption
Host-Madsen, Anders	Learning Source Coding for General Alphabets and Finite State Machines On Energy-Delay Tradeoff in Uncoordinated MAC
Hota, Ashish	Adaptive Identification from a Support Vector Perspective
How, Jonathan	Backward Reachability Analysis for Safety Verification of Neural Feedback Loops
Hu, Zhenhua	Straggler Exploitation in Distributed Computing Systems with Task Grouping
Huang, Chao	Verification and Design of Robust and Safe Neural Network-enabled Autonomous Systems
Huang, Shao-Lun	Robust Transfer Learning Based on Minimax Principle Optimal Error Exponent of Type-Based Distributed Hypothesis Testing over AWGN Channels
Huang, Shuai	Rotation-Invariant Correlation Features for 2D Sparse Unknown View Tomography
Huang, Yunshen	A Differential Dynamic Programming-based Approach for Balancing Energy and Time Optimality in Motion Planning
Huynh, Chelsea	Block-missing data in linear systems: An unbiased stochastic gradient descent approach
J
Jafarpour, Saber	Interaction-aware interval reachability of neural network controlled systems
Jain, Rahul	One-Shot Non-Catalytic Distributed Purity Distillation
Jalali, Shirin	Theoretical Analysis of Binary Masks in Snapshot Compressive Imaging Systems
Jamieson, Kevin	Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games
Javidi, Tara	A variational approach to federated and robust learning
Jedra, Yassir	Best Policy Identification in Linear MDPs
Jiang, Harry	DOLL: Distributed OnLine Learning Using Preemptible Instances
Jiao, Jiantao	Fine-Tuning Language Models with Advantage-Induced Policy Alignment
Jin, Chi	DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
Jin, Tao	Active Ranking without Strong Stochastic Transitivity
Joe-Wong, Carlee	DOLL: Distributed OnLine Learning Using Preemptible Instances Fedsoft: Soft clustered federated learning with proximal local updating
Johnston, Jeremy	A Curriculum Learning Approach to Optimization with Application to Downlink Beamforming
Jordan, Michael	Fine-Tuning Language Models with Advantage-Induced Policy Alignment
Ju, Peizhong	Theory on Forgetting and Generalization of Continual Learning
K
Kalathil, Dileep	Natural Actor-Critic for Robust Reinforcement Learning
Kang, Enoch Hyunwook	Bounded (O(1)) Regret Recommendation Learning via Synthetic Controls Oracle
Kara, Ali	Reinforcement Learning for Stochastic Control under Weak Feller Continuous Models and General Information Structures
Karbasi, Amin	Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
Kargin, Taylan	Wasserstein Distributionally Robust Regret-Optimal Control under Partial Observability
Katz, Sydney	Backward Reachability Analysis for Safety Verification of Neural Feedback Loops
Kaya, Ege Can	Relative Entropy Regularization for Robust Submodular Multi-Task Subset Selection
Kempe, David	Priorities and Quotas in Online Matching
Keshvari, Maryam	Distributed Storage Over a Public Channel: Trade-off between Privacy and Shared Key Lengths
Khaled, Ahmed	DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
Kiah, Han Mao	The Bee Identification Problem and DNA-Based Data Storage
Kilfoyle, Riley	Non-Linear Analog Coding for Image Transmission over Noisy Channels
Kim, Seonho	Fast max-affine regression via stochastic gradient descent
Kipnis, Alon	The Minimax Risk in Testing the Histogram of Discrete Distributions for Uniformity under Missing Ball Alternatives
Kochenderfer, Mykel	Backward Reachability Analysis for Safety Verification of Neural Feedback Loops
Kochman, Yuval	Quantum Key Distribution with State Replacement
Korlakai Vinayak, Ramya	Human-in-the-Loop Out-of-Distribution Detection with False Positive Rate Control
Kostina, Victoria	Coded Kalman Filtering Over Gaussian Channels with Feedback
Kosut, Oliver	The Saddle-Point Method in Differential Privacy
Kumar, Bhumesh	Participation Factor Analysis of Nonlinear Systems: Beyond Equilibria
Kumar, Nithish	Phase Transitions for Diversity in Stochastic Block Model Dynamics
Kumar, P. R.	The Reward Biased Method: An Optimism based Approach for Reinforcement Learning Bounded (O(1)) Regret Recommendation Learning via Synthetic Controls Oracle
Kurt, Mehmet	Data-Driven Sequential Change Detection in Privacy-Sensitive Networks
Kümmerle, Christian	Weights Matter: Linear & Superlinear Convergence Rates for IRLS in Low-Rank Optimization
L
Lam, Jason	Straggler Exploitation in Distributed Computing Systems with Task Grouping
Lathrop, James I.	Verifying Chemical Reaction Networks with the Isabelle Theorem Prover
Lauand, Caio	Inverse-Free Zap Stochastic Approximation
Le Phuc, Lu	New results on Erasure Combinatorial Batch Codes
Lee, Kiryung	Fast max-affine regression via stochastic gradient descent
Lee, Ulysses	Subspace Methods for Blind Fractionally-Spaced Equalization of Distributed Phase-Shift Beamforming Signals
Lesieutre, Bernard	Participation Factor Analysis of Nonlinear Systems: Beyond Equilibria
Letrouit, Cyril	Clustering in transformers: an interacting particle systems perspective
Leung, Chi Ho	Adaptive Identification from a Support Vector Perspective
Levin, Eitan	Any-dimensional convex sets
Li, Jiajun	Verification and Design of Robust and Safe Neural Network-enabled Autonomous Systems
Li, Wenchao	Verification and Design of Robust and Safe Neural Network-enabled Autonomous Systems
Li, Xiang	Complete Asymptotic Analysis for Projected Stochastic Approximation and Debiased Variants
Li, Xiaoou	Globally-optimal Greedy Experiment Selection For Active Sequential Estimation
Li, Xin	On $k$-Mer-Based and Maximum Likelihood Estimation Algorithms for Trace Reconstruction
Li, Zhaoyuan	Sequential Change-Point Detection for Correlation Matrices
Li, Zhi	Non-Linear Analog Coding for Image Transmission over Noisy Channels
Liang, Jiadong	Complete Asymptotic Analysis for Projected Stochastic Approximation and Debiased Variants
Liang, Yingbin	Theory on Forgetting and Generalization of Continual Learning
Lin, Heguang	Human-in-the-Loop Out-of-Distribution Detection with False Positive Rate Control
Lin, Sen	Theory on Forgetting and Generalization of Continual Learning
Lindemann, Lars	Conformal Prediction for STL Runtime Verification
Liu, Xiangyu	Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing
Liu, Xiaoyang	A Curriculum Learning Approach to Optimization with Application to Downlink Beamforming
Lou, Hao	Active Ranking without Strong Stochastic Transitivity
Love, David	Derandomizing Codes for the Binary Adversarial Wiretap Channel of Type II Preserving Sparsity and Privacy in Straggler-Resilient Distributed Matrix Computations
Low, Steven	Three-phase Transformer Modeling
Lykouris, Thodoris	Quantifying the Cost of Learning in Queueing Systems
Lykouris, Thodoris	Efficient decentralized multi-agent learning in asymmetric bipartite queueing systems
Lyu, Xue	Towards constrained grid-forming control
M
Ma, Anna	On Subsampled Quantile Randomized Kaczmarz Block-missing data in linear systems: An unbiased stochastic gradient descent approach
Ma, Cong	The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
Ma, Jianhao	Blessing of Nonconvexity in Factorized Models
Ma, Yinbin	Coded Caching with Linear Coded Placement: Exact Tradeoff for the Three User Case
Maguluri, Siva Theja	Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise
Maheshwari, Chinmay	Dynamic Tolling in Arc-based Traffic Assignment Models
Maiti, Arnab	Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games
Malak, Derya	An Achievable Low Complexity Encoding Scheme for Coloring Cyclic Graphs
Manitara, Nicolas	Privacy-Preserving Distributed k-means Clustering with Quantized Communication in Finite Time
Maranzatto, Thomas	A Unified Analysis of Dynamic Interactive Learning
Marden, Jason	Communication Enabled Collaborations in Multi-Agent Systems
Maros, Marie	A Unified View of Decentralized Algorithms for Sparse Linear Regression
Mathieu, Johanna	Quantifying Confidence in Electricity Rate Plan Recommendations Considering Variability in Future Electricity Usage
Matthews, Gretchen	Multishot Adversarial Network Decoding
Mete, Akshay	The Reward Biased Method: An Optimism based Approach for Reinforcement Learning
Meyn, Sean	Inverse-Free Zap Stochastic Approximation
Mishchenko, Konstantin	DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
Mohajer, Soheil	Distributed Optimization with Imperfect Information Sharing
Mokhtari, Aryan	On representation learning with the InfoNCE loss
Molloy, Timothy	Pulling Back from Infinity: Asymptotically Optimal Sampling of Infinite-Dimensional Measurements
Montanari, Andrea	Why interpolating neural nets generalize well: recent insights from neural tangent model
Moothedath, Shana	AltGDMin for Fast Federated Low Rank Matrix Completion
Morchdi, Chedi	Exploring Gradient Oscillation in Deep Neural Network Training
Mosterman, Pieter J.	Data-Driven Sequential Change Detection in Privacy-Sensitive Networks
Muller Vasconcelos, Marcos	Fundamental Limits of Strategic Coordination
N
Naghizadeh, Parinaz	United We Fall: On the Nash Equilibria of Multiplex Network Games
Nair, Girish	Pulling Back from Infinity: Asymptotically Optimal Sampling of Infinite-Dimensional Measurements
Nedich, Angelia	Characterization of Potential Games: Application in Aggregative Games
Neely, Michael	Adaptive optimization for stochastic renewal systems
Newton, Rachel	Manifold Optimization for Data Driven Reduced-Order Modeling
Ngo Dinh, Hy	New results on Erasure Combinatorial Batch Codes
Nguyen Dinh, Thuc	New results on Erasure Combinatorial Batch Codes
Nikbakht, Homa	Derandomizing Codes for the Binary Adversarial Wiretap Channel of Type II
O
Oechtering, Tobias J.	Multi-terminal Strong Coordination over Noiseless Networks with Secrecy Constraints
Ogbanna, Gerald	Aggregating Power Networks for Decentralized Control: A Spectral Clustering Approach
Oguchienti, Somtochukwu	Inverse Reinforcement Learning with Learning and Leveraging Demonstrators' Varying Expertise Levels
Oliva, Gabriele	Privacy-Preserving Distributed k-means Clustering with Quantized Communication in Finite Time
Ong, Lawrence	An Improved Greedy Cover Algorithm for Pliable Index Coding
Osera, Peter-Michael	Verifying Chemical Reaction Networks with the Isabelle Theorem Prover
Ozgur, Ayfer	Training generative models from privatized data
P
Paarporn, Keith	Non-myopic agents can stabilize cooperation in feedback-evolving games
Paccagnan, Dario	Communication Enabled Collaborations in Multi-Agent Systems
Paganini, Fernando	Dynamic Load Balancing of Selfish Drivers between Spatially Distributed Electrical Vehicle Charging Stations
Pajic, Miroslav	Vulnerability Analysis of Perception-Based Control: Modeling and Fundamental Limits
Pappas, George J.	Conformal Prediction for STL Runtime Verification
Parise, Francesca	Learning in Network Games with Dynamic Populations
Parulekar, Advait	On representation learning with the InfoNCE loss
Paré, Philip E.	Adaptive Identification from a Support Vector Perspective
Perez Avellaneda, Ivan	Backward and Inner Approximation of Output Reachable sets via Chen-Fliess Series
Pfister, Henry	Achieving Capacity on Non-Binary Channels with Generalized Reed–Muller Codes
Pham, Vinh	Coding for forensic 3D fingerprinting
Polyanskiy, Yury	Likelihood-free hypothesis testing Clustering in transformers: an interacting particle systems perspective
Poojary, Pawan	Bayesian Observational Learning in Mean-Field Games with Imperfect Observations
Poonawala, Hasan	Automated Stability Analysis of Piecewise Affine Dynamics Using Vertices
Poor, H. Vincent	Derandomizing Codes for the Binary Adversarial Wiretap Channel of Type II
Pradelski, Bary	Communication Enabled Collaborations in Multi-Agent Systems
Prater-Bennette, Ashley	Robust Average-Reward Markov Decision Processes
Proutiere, Alexandre	Best Policy Identification in Linear MDPs
Q
Qin, Xin	Conformal Prediction for STL Runtime Verification
Qin, Yilong	Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Markov Chains
Qiu, Deqiang	Rotation-Invariant Correlation Features for 2D Sparse Unknown View Tomography
Qu, Qing	The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks
R
Rabbat, Michael	Explorations on scalable preconditioned gradient methods for deep learning
Racz, Miklos	"All-Something-Nothing" Phase Transitions in Planted Subgraph Recovery
Ramachandran, Viswanathan	Multi-terminal Strong Coordination over Noiseless Networks with Secrecy Constraints
Ramamoorthy, Aditya	Preserving Sparsity and Privacy in Straggler-Resilient Distributed Matrix Computations
Ramishetty, Sravani	High Probability Guarantees For Federated Learning.
Ramkumar, Vinayak	Coefficient Complexity in Low-Access Quantized Linear Computations
Ranade, Gireeja	Phase Transitions for Diversity in Stochastic Block Model Dynamics
Rao, Shrisha	Near Optimal Differentially Private Client Selection in Federated Settings
Ratliff, Lillian	Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games
Ravagnani, Alberto	Multishot Adversarial Network Decoding
Raviv, Netanel	Coding for forensic 3D fingerprinting Coefficient Complexity in Low-Access Quantized Linear Computations
Ray, Ruchira	Asymptotics for alpha-posteriors with applications to variational inference
Rebrova, Elizaveta	On Subsampled Quantile Randomized Kaczmarz
Reeves, Galen	Achieving Capacity on Non-Binary Channels with Generalized Reed–Muller Codes
Reisizadeh, Hadi	Distributed Optimization with Imperfect Information Sharing
Reshetova, Daria	Training generative models from privatized data
Reyzin, Lev	A Unified Analysis of Dynamic Interactive Learning
Rigollet, Philippe	Clustering in transformers: an interacting particle systems perspective
Rikos, Apostolos	Privacy-Preserving Distributed k-means Clustering with Quantized Communication in Finite Time
Risteski, Andrej	Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Markov Chains
Rober, Nicholas	Backward Reachability Analysis for Safety Verification of Neural Feedback Loops
Rokade, Kiran	Learning in Network Games with Dynamic Populations
Rosen, David	Practical Algorithms for Globally Optimal Geometric Machine Perception
Rout, Litu	Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD
Ruan, Yichen	Fedsoft: Soft clustered federated learning with proximal local updating
Rush, Cynthia	Asymptotics for alpha-posteriors with applications to variational inference
Ruzomberka, Eric	Derandomizing Codes for the Binary Adversarial Wiretap Channel of Type II
Ryu, Jongha Jon	Group Fairness with Uncertainty in Sensitive Attributes
S
Sabag, Oron	Coded Kalman Filtering Over Gaussian Channels with Feedback
Sadeghi, Parastoo	An Improved Greedy Cover Algorithm for Pliable Index Coding
Samanipour, Pouya	Automated Stability Analysis of Piecewise Affine Dynamics Using Vertices
Sandon, Colin	"All-Something-Nothing" Phase Transitions in Planted Subgraph Recovery
Sanghavi, Sujay	Understanding Self Distillation
Sankar, Lalitha	The Saddle-Point Method in Differential Privacy
Sastry, Shankar	Dynamic Tolling in Arc-based Traffic Assignment Models
Sattigeri, Prasanna	Group Fairness with Uncertainty in Sensitive Attributes
Sayin, Muhammed	Convergence of Heterogeneous Learning Dynamics in Zero-sum Stochastic Games
Schmidt, Addison W.	Verifying Chemical Reaction Networks with the Isabelle Theorem Prover
Scutari, Gesualdo	A Unified View of Decentralized Algorithms for Sparse Linear Regression
Seiler, Peter	Analysis of Neural Network Controllers Using Quadratic Constraints Manifold Optimization for Data Driven Reduced-Order Modeling
Sen, Pranab	One-Shot Non-Catalytic Distributed Purity Distillation
Shah, Abhin	Group Fairness with Uncertainty in Sensitive Attributes On counterfactual inference with unobserved confounding
Shah, Devavrat	On counterfactual inference with unobserved confounding
Shakkottai, Sanjay	Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD On representation learning with the InfoNCE loss
Shanmugam, Karthikeyan	On representation learning with the InfoNCE loss
Shapiro, Julia	Multishot Adversarial Network Decoding
Sharma, Hiteshi	Fine-Tuning Language Models with Advantage-Induced Policy Alignment
Shayevitz, Ofer	Quantum Key Distribution with State Replacement
Shen, Maohao	Group Fairness with Uncertainty in Sensitive Attributes
Shen, Yandi	The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
Shen, Yu-Chen	Privacy Amplification Against Quantum Side Information Via Regular Random Binning
Shi, Guanya	Leveraging Predictions in Power System Frequency Control: an Adaptive Approach
Shi, Hao-Jun Michael	Explorations on scalable preconditioned gradient methods for deep learning
Shi, Yuanyuan	Leveraging Predictions in Power System Frequency Control: an Adaptive Approach
Shojaeighadikolaei, Amin	An Efficient Distributed Multi-Agent Reinforcement Learning for EV Charging Network Control
Shroff, Ness	Theory on Forgetting and Generalization of Continual Learning
Shukla, Dhirendra	Communication-efficient Federated Multi-resource Allocation: A Non-homogeneous Markov Chain Model Near Optimal Differentially Private Client Selection in Federated Settings
Sidrane, Chelsea	Backward Reachability Analysis for Safety Verification of Neural Feedback Loops
Sima, Jin	Coding for forensic 3D fingerprinting
Singh, Ankit Pratap	Byzantine-resilient Federated Low Rank Column-wise Compressive Sensing
Singh, Rahul	The Reward Biased Method: An Optimism based Approach for Reinforcement Learning
Skoglund, Mikael	Multi-terminal Strong Coordination over Noiseless Networks with Secrecy Constraints
Slater, Jesse C.	Verifying Chemical Reaction Networks with the Isabelle Theorem Prover
Soltanalian, Mojtaba	Deep Learning Meets Adaptive Filtering: A Stein's Unbiased Risk Estimator Approach
Srivastava, Arunabh	Age of Gossip on a Grid
Strand, Michael	Block-missing data in linear systems: An unbiased stochastic gradient descent approach
Stöger, Dominik	Weights Matter: Linear & Superlinear Convergence Rates for IRLS in Low-Rank Optimization
Su, Lili	A Non-parametric View of FedAvg and FedProx: Beyond Stationary Points
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