← Authors

Vikas Sindhwani

46 papers · 2006–2025 · 11 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (7) 🐝 Cross-Pollinator (14) πŸ—ΊοΈ Taxonomy Completionist (29) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (11) πŸƒ Academic Marathon (19) 🌟 Keyword Trendsetter Combo (4) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution πŸ† Keyword Champion πŸ‘₯ Mega-Team (34) πŸ’Ž Century Club (46) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (99) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (13)

Conferences

NIPS (13) CORL (10) ICML (6) JMLR (4) RSS (4) L4DC (3) ICLR (2) ACL (1) AISTATS (1) CVPR (1) IJCNLP (1)

Top co-authors

Deepali Jain (8) Krzysztof Choromanski (7) Sumeet Singh (7) Krzysztof Marcin Choromanski (6) Jie Tan (5) Tingnan Zhang (5) Haim Avron (5) Dmitry Kalashnikov (5) Adrian Weller (5) Atil Iscen (4)

Research topics

Reinforcement Learning (2)

Keywords

kernel methods (7) blackbox optimization (4) kernel approximation (4) semi-supervised learning (4) model predictive control (3) policy optimization (3) support vector machine (3) compressed sensing (2) derivative-free optimization (2) dynamical system (2) orthogonal matching pursuit (2) margin maximization (2) neural network optimization (2) reinforcement learning (2) matrix factorization (2) group sparsity (2) sim-to-real transfer (2) non-convex optimization (2) model compression (2) imitation learning (2)

Papers

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
Modeling the Real World with High-Density Visual Particle Dynamics CORL 2024
Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning NIPS 2024
Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs CORL 2024
Demonstrating Large Language Models on Robots RSS 2023
Robotic Table Tennis: A Case Study into a High Speed Learning System RSS 2023
Mnemosyne: Learning to Train Transformers with Transformers NIPS 2023
Agile Catching with Whole-Body MPC and Blackbox Policy Learning L4DC 2023
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language ICLR 2023
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation CORL 2022
Hybrid Random Features ICLR 2022
Safely Learning Dynamical Systems from Short Trajectories L4DC 2021
Learning Stability Certificates from Data CORL 2020
Ode to an ODE NIPS 2020
Transporter Networks: Rearranging the Visual World for Robotic Manipulation CORL 2020
Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint L4DC 2020
Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020
Data Efficient Reinforcement Learning for Legged Robots CORL 2019
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization NIPS 2019
Teleoperator Imitation with Continuous-Time Safety RSS 2019
Provably Robust Blackbox Optimization for Reinforcement Learning CORL 2019
Policies Modulating Trajectory Generators CORL 2018
The Geometry of Random Features AISTATS 2018
Structured Evolution with Compact Architectures for Scalable Policy Optimization ICML 2018
On Blackbox Backpropagation and Jacobian Sensing NIPS 2017
Geometry of 3D Environments and Sum of Squares Polynomials RSS 2017
Hierarchically Compositional Kernels for Scalable Nonparametric Learning JMLR 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 NIPS 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 NIPS 2013
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels NIPS 2011
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference NIPS 2010
A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge ACL 2009
A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge IJCNLP 2009
Optimization Techniques for Semi-Supervised Support Vector Machines JMLR 2008
Regularized Co-Clustering with Dual Supervision NIPS 2008
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples JMLR 2006
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NIPS 2006
Relational Learning with Gaussian Processes NIPS 2006
Branch and Bound for Semi-Supervised Support Vector Machines NIPS 2006