Vikas Sindhwani

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

Achievements

+15 more ↓

🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (29) 🐣 Hot Topic Early Bird

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (11) 🏃 Academic Marathon (19) 🌟 Keyword Trendsetter Combo (4) 🌱 Topic Pioneer 🔬 Deep Specialist (10) 🧬 Topic Evolution 🏆 Keyword Champion 👥 Mega-Team (34) 💎 Century Club (46) 🚀 Conference Pioneer 📈 Trend Setter 🗃️ Keyword Collector (99) ⚡ Prolific Year (5) 🔥 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