Hypergradient Optimization

Latest papers

11 papers1 paper in the last four weeks, with none the four weeks before. 0.0% of all new papers.

LEAP: Gradient Flow Augmented Lagrangian Trajectory Optimization for Contact Constrained Robots
Oct 14, 2026César E. Ramos Chuquiure, Ryan Tsai, Yutong Zhou +8Hypergradient Optimization Trajectory Optimization
Department of Robotics, University of Michigan, Ann Arbor, MI, USA. · Computer Science and Engineering, University of Michigan, Ann Arbor, MI, USA. · Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.
Bilevel Optimization of Topology and Hyperparameters (BOTH)
Sep 18, 2026Suryanarayanan Manoj Sanu, Miguel Anibal Bessa, Alejandro Marcos AragónHypergradient Optimization Topology Optimization
Faculty of Mechanical Engineering Delft university of technology Delft The Netherlands · School of engineering Brown University Providence United States of America
Efficient Hypergradient Descent for Inverse Reinforcement Learning
Aug 11, 2026Nikita Sevriukov, Anna Barabanova, Uliana Gagarina +4Reinforcement Learning Gradient Descent
HSE University Moscow, Russia
Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks
Aug 10, 2026Binchuan QiGradient Descent Neural Network Optimization
College of Electronics and Information Engineering Tongji University Shanghai, 200092, China
Hypergradient-based Bilevel Reinforcement Learning with Improved Sample Complexity
Jul 30, 2026Naman Saxena, Mudit Gaur, Vaneet AggarwalReinforcement Learning Hypergradient Optimization
Purdue University West Lafayette, IN 47907
Semiparametric Efficient Bilevel Gradient Estimation
May 20, 2026Fares El Khoury, Houssam Zenati, Nathan Kallus +2Semiparametric Inference Hypergradient Optimization
Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK · Gatsby Computational Neuroscience Unit, University College London · Cornell University +1
Federated Learning with Hypergradient-based Online Update of Aggregation Weights
May 1, 2026Ayano Nakai-Kasai, Tadashi WadayamaFederated Learning Aggregation Hypergradient Optimization
Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555, Japan
FlowAdam: Implicit Regularization via Geometry-Aware Soft Momentum Injection
Apr 8, 2026Devender Singh, Tarun SheelHypergradient Optimization Adaptive Gradient Methods
Department of Computer Science Memorial University of Newfoundland St. John’s, NL, Canada · Department of Mathematics and Statistics Memorial University of Newfoundland St. John’s, NL, Canada
Efficient Bilevel Optimization with KFAC-Based Hypergradients
Mar 31, 2026Disen Liao, Felix Dangel, Yaoliang YuKronecker-Factored Approximation Bilevel Optimization
University of Waterloo · Vector Institute
Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning
Mar 16, 2026Mikoto Kudo, Takumi Tanabe, Akifumi Wachi +1Hypergradient Optimization Decentralized MARL
University of Tsukuba · RIKEN AIP · LY Corporation
Understanding the Generalization of Bilevel Programming in Hyperparameter Optimization: A Tale of Bias-Variance Decomposition
Feb 20, 2026Yubo Zhou, Jun Shu, Junmin Liu +1Hypergradient Optimization Hyperparameter Optimization
School of Mathematics and Statistics and Ministry of Education Key Lab of Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, 100190, Shaan’xi Province, P. R. China. · Pazhou Lab (Huangpu), Street, Guangzhou, Guangdong Province, P. R. China.

Oct 14, 2026J/K move · Enter open · S save

LEAP: Gradient Flow Augmented Lagrangian Trajectory Optimization for Contact Constrained Robots

César E. Ramos Chuquiure, Ryan Tsai, Yutong Zhou, Zihang Huang+7

Department of Robotics, University of Michigan, Ann Arbor, MI, USA. · Computer Science and Engineering, University of Michigan, Ann Arbor, MI, USA. · Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.

Hypergradient Optimization Trajectory Optimization Robotic Optimization Augmented Lagrangian Method Robot Locomotion

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Generating dynamically feasible motions for legged and manipulating robots requires solving a large, nonlinear, non-convex optimal control problem (OCP) in which contact wrenches must satisfy friction-cone constraints throughout the motion, not only at isolated instants. Existing solvers are sensitive to the initial guess and scale poorly with the number of joints. This paper introduces LEAP, which transcribes the OCP with pseudospectral collocation and, instead of a Newton or SQP solve, integrates a primal--dual gradient flow of a Powell--Hestenes--Rockafellar augmented Lagrangian to compute a solution. Because the flow is stiff, this paper designs a linearly implicit integrator with a Gauss--Newton metric, momentum, and a merit-based step controller that keeps the augmented Lagrangian monotone. Across locomotion benchmarks on five robot platforms, from planar hoppers to 32-joint humanoids, LEAP is the only method to solve every tested problem, achieves substantial speedups over Crocoddyl and Aligator on several benchmarks, and reaches trackable references at smaller compute budgets. The resulting trajectories are validated by tracking them in a high-fidelity simulator and on hardware. We will make the code public upon final acceptance of this paper.