Vikas Sindhwani

Generating Robot Constitutions & Benchmarks for Semantic Safety CoRL 2025 Learning the RoPEs: Better 2D and 3D Position Encodings with STRING ICML 2025 Predictive Red Teaming: Breaking Policies Without Breaking Robots CoRL 2025 Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs CoRL 2024 Modeling the Real World with High-Density Visual Particle Dynamics CoRL 2024 Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning NeurIPS 2024 Agile Catching with Whole-Body MPC and Blackbox Policy Learning L4DC 2023 Demonstrating Large Language Models on Robots RSS 2023 Mnemosyne: Learning to Train Transformers with Transformers NeurIPS 2023 Robotic Table Tennis: A Case Study into a High Speed Learning System RSS 2023 Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language ICLR 2023 Hybrid Random Features ICLR 2022 Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation CoRL 2022 Safely Learning Dynamical Systems from Short Trajectories L4DC 2021 Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint L4DC 2020 Learning Stability Certificates from Data CoRL 2020 Ode to an ODE NeurIPS 2020 Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020 Transporter Networks: Rearranging the Visual World for Robotic Manipulation CoRL 2020 Data Efficient Reinforcement Learning for Legged Robots CoRL 2019 From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization NeurIPS 2019 Provably Robust Blackbox Optimization for Reinforcement Learning CoRL 2019 Teleoperator Imitation with Continuous-Time Safety RSS 2019 Policies Modulating Trajectory Generators CoRL 2018 Structured Evolution with Compact Architectures for Scalable Policy Optimization ICML 2018 The Geometry of Random Features AISTATS 2018 Geometry of 3D Environments and Sum of Squares Polynomials RSS 2017 Hierarchically Compositional Kernels for Scalable Nonparametric Learning JMLR 2017 On Blackbox Backpropagation and Jacobian Sensing NeurIPS 2017 Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels JMLR 2016 Recycling Randomness with Structure for Sublinear time Kernel Expansions ICML 2016 Structured Transforms for Small-Footprint Deep Learning NeurIPS 2015 Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels ICML 2014 Random Laplace Feature Maps for Semigroup Kernels on Histograms CVPR 2014 Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization ICML 2013 Sketching Structured Matrices for Faster Nonlinear Regression NeurIPS 2013 Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels NeurIPS 2011 Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference NeurIPS 2010 A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge ACL 2009 Optimization Techniques for Semi-Supervised Support Vector Machines JMLR 2008 Regularized Co-Clustering with Dual Supervision NeurIPS 2008 An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NeurIPS 2006 Branch and Bound for Semi-Supervised Support Vector Machines NeurIPS 2006 Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples JMLR 2006 Relational Learning with Gaussian Processes NeurIPS 2006