Vikas Sindhwani

According to our database1, Vikas Sindhwani authored at least 109 papers between 2001 and 2024.

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Bibliography

2024
Achieving Human Level Competitive Robot Table Tennis.
CoRR, 2024

Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs.
CoRR, 2024

Modeling the Real World with High-Density Visual Particle Dynamics.
CoRR, 2024

Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning.
CoRR, 2024

Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity.
CoRR, 2024

SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
Single-Level Differentiable Contact Simulation.
IEEE Robotics Autom. Lett., July, 2023

Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models.
CoRR, 2023

Robotic Table Tennis: A Case Study into a High Speed Learning System.
CoRR, 2023

Barkour: Benchmarking Animal-level Agility with Quadruped Robots.
CoRR, 2023

Safely Learning Dynamical Systems.
CoRR, 2023

Demonstrating Large Language Models on Robots.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023


Mnemosyne: Learning to Train Transformers with Transformers.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Agile Catching with Whole-Body MPC and Blackbox Policy Learning.
Proceedings of the Learning for Dynamics and Control Conference, 2023

A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Trajectory Optimization with Optimization-Based Dynamics.
IEEE Robotics Autom. Lett., 2022

Implicit Two-Tower Policies.
CoRR, 2022

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language.
CoRR, 2022

Multiscale Sensor Fusion and Continuous Control with Neural CDEs.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Optimizing Trajectories with Closed-Loop Dynamic SQP.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Hybrid Random Features.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation.
Proceedings of the Conference on Robot Learning, 2022

2021
Learning stabilizable nonlinear dynamics with contraction-based regularization.
Int. J. Robotics Res., 2021

Safely Learning Dynamical Systems from Short Trajectories.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Piecewise-Linear Motion Planning amidst Static, Moving, or Morphing Obstacles.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020
An Ode to an ODE.
CoRR, 2020

Time Dependence in Non-Autonomous Neural ODEs.
CoRR, 2020

Ode to an ODE.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Robotic Table Tennis with Model-Free Reinforcement Learning.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Unsupervised Anomaly Detection for Self-flying Delivery Drones.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Stochastic Flows and Geometric Optimization on the Orthogonal Group.
Proceedings of the 37th International Conference on Machine Learning, 2020

Transporter Networks: Rearranging the Visual World for Robotic Manipulation.
Proceedings of the 4th Conference on Robot Learning, 2020

Learning Stability Certificates from Data.
Proceedings of the 4th Conference on Robot Learning, 2020

2019
Teleoperator Imitation with Continuous-time Safety.
CoRR, 2019

When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies.
CoRR, 2019

Teleoperator Imitation with Continuous-Time Safety.
Proceedings of the Robotics: Science and Systems XV, 2019

From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Data Efficient Reinforcement Learning for Legged Robots.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Provably Robust Blackbox Optimization for Reinforcement Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018
Learning Contracting Vector Fields For Stable Imitation Learning.
CoRR, 2018

Learning Stabilizable Dynamical Systems via Control Contraction Metrics.
Proceedings of the Algorithmic Foundations of Robotics XIII, 2018

Learning-based Air Data System for Safe and Efficient Control of Fixed-wing Aerial Vehicles.
Proceedings of the 2018 IEEE International Symposium on Safety, 2018

Optimizing Simulations with Noise-Tolerant Structured Exploration.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Structured Evolution with Compact Architectures for Scalable Policy Optimization.
Proceedings of the 35th International Conference on Machine Learning, 2018

Policies Modulating Trajectory Generators.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

The Geometry of Random Features.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Recommender Systems.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Hierarchically Compositional Kernels for Scalable Nonparametric Learning.
J. Mach. Learn. Res., 2017

Manifold Regularization for Kernelized LSTD.
CoRR, 2017

Geometry of 3D Environments and Sum of Squares Polynomials.
Proceedings of the Robotics: Science and Systems XIII, 2017

On Blackbox Backpropagation and Jacobian Sensing.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sequential operator splitting for constrained nonlinear optimal control.
Proceedings of the 2017 American Control Conference, 2017

2016
High-Performance Kernel Machines With Implicit Distributed Optimization and Randomization.
Technometrics, 2016

Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels.
J. Mach. Learn. Res., 2016

Recycling Randomness with Structure for Sublinear time Kernel Expansions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning compact recurrent neural networks.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015
Near-separable Non-negative Matrix Factorization with ℓ<sub>1</sub> and Bregman Loss Functions.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Structured Transforms for Small-Footprint Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Learning Machines Implemented on Non-Deterministic Hardware.
CoRR, 2014

Personalized classifiers: evolving a classifier from a large reference knowledge graph.
Proceedings of the 18th International Database Engineering & Applications Symposium, 2014

Kernel methods match Deep Neural Networks on TIMIT.
Proceedings of the IEEE International Conference on Acoustics, 2014

Random Laplace Feature Maps for Semigroup Kernels on Histograms.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Sketching Structured Matrices for Faster Nonlinear Regression.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization.
Proceedings of the 30th International Conference on Machine Learning, 2013

Low-rank matrix factorization for Deep Neural Network training with high-dimensional output targets.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Scalable Matrix-valued Kernel Learning and High-dimensional Nonlinear Causal Inference
CoRR, 2012

Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization.
Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

Large-scale distributed non-negative sparse coding and sparse dictionary learning.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Extracting insights from social media with large-scale matrix approximations.
IBM J. Res. Dev., 2011

Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Concept Labeling: Building Text Classifiers with Minimal Supervision.
Proceedings of the IJCAI 2011, 2011

Vector-valued Manifold Regularization.
Proceedings of the 28th International Conference on Machine Learning, 2011

SystemML: Declarative machine learning on MapReduce.
Proceedings of the 27th International Conference on Data Engineering, 2011

Emerging topic detection using dictionary learning.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

2010
Recommender Systems.
Proceedings of the Encyclopedia of Machine Learning, 2010

Bridging Domains with Words: Opinion Analysis with Matrix Tri-factorizations.
Proceedings of the SIAM International Conference on Data Mining, 2010

Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

One-Class Matrix Completion with Low-Density Factorizations.
Proceedings of the ICDM 2010, 2010

2009
Multiview point cloud kernels for semisupervised learning [Lecture Notes].
IEEE Signal Process. Mag., 2009

Winning the KDD Cup Orange Challenge with Ensemble Selection.
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

Leveraging social networks for corporate staffing and expert recommendation.
IBM J. Res. Dev., 2009

Knowledge transformation for cross-domain sentiment classification.
Proceedings of the 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2009

Uncertainty sampling and transductive experimental design for active dual supervision.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework.
Proceedings of the ICDM Workshops 2009, 2009

A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge.
Proceedings of the ACL 2009, 2009

2008
Optimization Techniques for Semi-Supervised Support Vector Machines.
J. Mach. Learn. Res., 2008

Regularized Co-Clustering with Dual Supervision.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

An RKHS for multi-view learning and manifold co-regularization.
Proceedings of the Machine Learning, 2008

Document-Word Co-regularization for Semi-supervised Sentiment Analysis.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007
Semi-Supervised Gaussian Process Classifiers.
Proceedings of the IJCAI 2007, 2007

2006
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples.
J. Mach. Learn. Res., 2006

Large scale semi-supervised linear SVMs.
Proceedings of the SIGIR 2006: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2006

An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Relational Learning with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Branch and Bound for Semi-Supervised Support Vector Machines.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Deterministic annealing for semi-supervised kernel machines.
Proceedings of the Machine Learning, 2006

The Geometric Basis of Semi-Supervised Learning.
Proceedings of the Semi-Supervised Learning, 2006

2005
Beyond the point cloud: from transductive to semi-supervised learning.
Proceedings of the Machine Learning, 2005

On Manifold Regularization.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Feature selection in MLPs and SVMs based on maximum output information.
IEEE Trans. Neural Networks, 2004

2001
Information Theoretic Feature Crediting in Multiclass Support Vector Machines.
Proceedings of the First SIAM International Conference on Data Mining, 2001


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