
Learning to Rearrange Deformable Cables, Fabrics, and Bags with GoalConditioned Transporter Networks
Rearranging and manipulating deformable objects such as cables, fabrics,...
read it

Safely Learning Dynamical Systems from Short Trajectories
A fundamental challenge in learning to control an unknown dynamical syst...
read it

Transporter Networks: Rearranging the Visual World for Robotic Manipulation
Robotic manipulation can be formulated as inducing a sequence of spatial...
read it

PiecewiseLinear Motion Planning amidst Static, Moving, or Morphing Obstacles
We propose a novel method for planning shortest length piecewiselinear ...
read it

Learning Stability Certificates from Data
Many existing tools in nonlinear control theory for establishing stabili...
read it

An Ode to an ODE
We present a new paradigm for Neural ODE algorithms, calledODEtoODE, whe...
read it

Time Dependence in NonAutonomous Neural ODEs
Neural Ordinary Differential Equations (ODEs) are elegant reinterpretati...
read it

Robotic Table Tennis with ModelFree Reinforcement Learning
We propose a modelfree algorithm for learning efficient policies capabl...
read it

Stochastic Flows and Geometric Optimization on the Orthogonal Group
We present a new class of stochastic, geometricallydriven optimization ...
read it

Policies Modulating Trajectory Generators
We propose an architecture for learning complex controllable behaviors b...
read it

Learning Stabilizable Nonlinear Dynamics with ContractionBased Regularization
We propose a novel framework for learning stabilizable nonlinear dynamic...
read it

Data Efficient Reinforcement Learning for Legged Robots
We present a modelbased framework for robot locomotion that achieves wa...
read it

Teleoperator Imitation with Continuoustime Safety
Learning to effectively imitate human teleoperators, with generalization...
read it

Adaptive SampleEfficient Blackbox Optimization via ESactive Subspaces
We present a new algorithm ASEBO for conducting optimization of highdim...
read it

When random search is not enough: SampleEfficient and NoiseRobust Blackbox Optimization of RL Policies
Interest in derivativefree optimization (DFO) and "evolutionary strateg...
read it

Learning Stabilizable Dynamical Systems via Control Contraction Metrics
We propose a novel framework for learning stabilizable nonlinear dynamic...
read it

Optimizing Simulations with NoiseTolerant Structured Exploration
We propose a simple dropin noisetolerant replacement for the standard ...
read it

Learning Contracting Vector Fields For Stable Imitation Learning
We propose a new nonparametric framework for learning incrementally sta...
read it

Structured Evolution with Compact Architectures for Scalable Policy Optimization
We present a new method of blackbox optimization via gradient approximat...
read it

Manifold Regularization for Kernelized LSTD
Policy evaluation or value function or Qfunction approximation is a key...
read it

Geometry of 3D Environments and Sum of Squares Polynomials
Motivated by applications in robotics and computer vision, we study prob...
read it

Hierarchically Compositional Kernels for Scalable Nonparametric Learning
We propose a novel class of kernels to alleviate the high computational ...
read it

Recycling Randomness with Structure for Sublinear time Kernel Expansions
We propose a scheme for recycling Gaussian random vectors into structure...
read it

Learning Compact Recurrent Neural Networks
Recurrent neural networks (RNNs), including long shortterm memory (LSTM...
read it

Structured Transforms for SmallFootprint Deep Learning
We consider the task of building compact deep learning pipelines suitabl...
read it

QuasiMonte Carlo Feature Maps for ShiftInvariant Kernels
We consider the problem of improving the efficiency of randomized Fourie...
read it

Scalable Matrixvalued Kernel Learning for Highdimensional Nonlinear Multivariate Regression and Granger Causality
We propose a general matrixvalued multiple kernel learning framework fo...
read it

Nearseparable Nonnegative Matrix Factorization with ℓ_1 and Bregman Loss Functions
Recently, a family of tractable NMF algorithms have been proposed under ...
read it

Fast Conical Hull Algorithms for Nearseparable Nonnegative Matrix Factorization
The separability assumption (Donoho & Stodden, 2003; Arora et al., 2012)...
read it

Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization
We describe novel subgradient methods for a broad class of matrix optimi...
read it