Papers
A Pontryagin Perspective on Reinforcement Learning
Onno Eberhard, Claire Vernade, Michael Muehlebach
Anytime Safe Reinforcement Learning
Pol Mestres, Arnau Marzabal, Jorge Cortes
Formation Shape Control using the Gromov-Wasserstein Metric
Haruto Nakashima, Siddhartha Ganguly, Kohei Morimoto et al.
Safe, Out-of-Distribution-Adaptive MPC with Conformalized Neural Network Ensembles
Jose Leopoldo Contreras, Ola Shorinwa, Mac Schwager
Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems
Luke Bhan, Peijia Qin, Miroslav Krstic et al.
Controlling Participation in Federated Learning with Feedback
Michael Cummins, Guner Dilsad Er, Michael Muehlebach
Orthogonal projection-based regularization for efficient model augmentation
Bendeguz Mate Györök, Jan H. Hoekstra, Johan Kon et al.
Learning for Layered Safety-Critical Control with Predictive Control Barrier Functions
William D. Compton, Max H. Cohen, Aaron D. Ames
Scalable Natural Policy Gradient for General-Sum Linear Quadratic Games with Known Parameters
Mostafa Shibl, Wesley Suttle, Vijay Gupta
Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots
Feihan Li, Abulikemu Abuduweili, Yifan Sun et al.
The Complexity of Sequential Prediction in Dynamical Systems
Vinod Raman, Unique Subedi, Ambuj Tewari
Learning Two-agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control
Hansung Kim, Edward L. Zhu, Chang Seok Lim et al.
Interacting Particle Systems for Fast Linear Quadratic RL
Anant A. Joshi, Heng-Sheng Chang, Amirhossein Taghvaei et al.
Learning Temporal Logic Predicates from Data with Statistical Guarantees
Emi Soroka, Rohan Sinha, Sanjay Lall
Asymptotics of Linear Regression with Linearly Dependent Data
Behrad Moniri, Hamed Hassani
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization
Anjian Li, Zihan Ding, Adji Bousso Dieng et al.
Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning
Batuhan Yardim, Niao He
Multi-agent Stochastic Bandits Robust to Adversarial Corruptions
Fatemeh Ghaffari, Xuchuang Wang, Jinhang Zuo et al.
State space models, emergence, and ergodicity: How many parameters are needed for stable predictions?
Ingvar Ziemann, Nikolai Matni, George Pappas
Certified Machine Unlearning Under High Dimensional Regime
Haolin Zou, Arnab Auddy, Yongchan Kwon et al.
FusionBench: A Unified Library and Comprehensive Benchmark for Deep Model Fusion
Anke Tang, Li Shen, Yong Luo et al.
Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients
Sachin Garg, Albert S. Berahas, Michał Dereziński
Gradient Equilibrium in Online Learning: Theory and Applications
Anastasios N. Angelopoulos, Michael I. Jordan, Ryan J. Tibshirani