Vikas Sindhwani

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 90

Top Venues

CoRR

ICRA

CoRL

ICML

Publications

Hao-Tien Lewis Chiang, Zhuo Xu, Zipeng Fu, Mithun George Jacob, Tingnan Zhang, Tsang-Wei Edward Lee, Wenhao Yu, Connor Schenck, David Rendleman, Dhruv Shah, Fei Xia, Jasmine Hsu, Jonathan Hoech, Pete Florence, Sean Kirmani, Sumeet Singh, Vikas Sindhwani, Carolina Parada, Chelsea Finn, Peng Xu, Sergey Levine, Jie Tan
Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. CoRR (2024)
Jake Varley, Sumeet Singh, Deepali Jain, Krzysztof Choromanski, Andy Zeng, Somnath Basu Roy Chowdhury, Avinava Dubey, Vikas Sindhwani
Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity. CoRR (2024)
William F. Whitney, Jacob Varley, Deepali Jain, Krzysztof Choromanski, Sumeet Singh, Vikas Sindhwani
Modeling the Real World with High-Density Visual Particle Dynamics. CoRR (2024)
Arijit Sehanobish, Avinava Dubey, Krzysztof Choromanski, Somnath Basu Roy Chowdhury, Deepali Jain, Vikas Sindhwani, Snigdha Chaturvedi
Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning. CoRR (2024)
Isabel Leal, Krzysztof Choromanski, Deepali Jain, Avinava Dubey, Jake Varley, Michael S. Ryoo, Yao Lu, Frederick Liu, Vikas Sindhwani, Quan Vuong, Tamás Sarlós, Ken Oslund, Karol Hausman, Kanishka Rao
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. ICRA (2024)
Montserrat Gonzalez Arenas, Ted Xiao, Sumeet Singh, Vidhi Jain, Allen Z. Ren, Quan Vuong, Jake Varley, Alexander Herzog, Isabel Leal, Sean Kirmani, Mario Prats, Dorsa Sadigh, Vikas Sindhwani, Kanishka Rao, Jacky Liang, Andy Zeng
How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies. ICRA (2024)
Deepali Jain, Krzysztof Marcin Choromanski, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan, Avinava Dubey
Mnemosyne: Learning to Train Transformers with Transformers. CoRR (2023)
Isabel Leal, Krzysztof Choromanski, Deepali Jain, Avinava Dubey, Jake Varley, Michael S. Ryoo, Yao Lu, Frederick Liu, Vikas Sindhwani, Quan Vuong, Tamás Sarlós, Ken Oslund, Karol Hausman, Kanishka Rao
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. CoRR (2023)
Deepali Jain, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan
Mnemosyne: Learning to Train Transformers with Transformers. NeurIPS (2023)
Ken Caluwaerts, Atil Iscen, J. Chase Kew, Wenhao Yu, Tingnan Zhang, Daniel Freeman, Kuang-Huei Lee, Lisa Lee, Stefano Saliceti, Vincent Zhuang, Nathan Batchelor, Steven Bohez, Federico Casarini, Jose Enrique Chen, Omar Cortes, Erwin Coumans, Adil Dostmohamed, Gabriel Dulac-Arnold, Alejandro Escontrela, Erik Frey, Roland Hafner, Deepali Jain, Bauyrjan Jyenis, Yuheng Kuang, Tsang-Wei Edward Lee, Linda Luu, Ofir Nachum, Ken Oslund, Jason Powell, Diego Reyes, Francesco Romano, Fereshteh Sadeghi, Ron Sloat, Baruch Tabanpour, Daniel Zheng, Michael Neunert, Raia Hadsell, Nicolas Heess, Francesco Nori, Jeff Seto, Carolina Parada, Vikas Sindhwani, Vincent Vanhoucke, Jie Tan
Barkour: Benchmarking Animal-level Agility with Quadruped Robots. CoRR (2023)
Andy Zeng, Brian Ichter, Fei Xia, Ted Xiao, Vikas Sindhwani
Demonstrating Large Language Models on Robots. Robotics: Science and Systems (2023)
Thomas Lew, Sumeet Singh, Mario Prats, Jeffrey Bingham, Jonathan Weisz, Benjie Holson, Xiaohan Zhang, Vikas Sindhwani, Yao Lu, Fei Xia, Peng Xu, Tingnan Zhang, Jie Tan, Montserrat Gonzalez
Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization. ICRA (2023)
Saminda Abeyruwan, Alex Bewley, Nicholas M. Boffi, Krzysztof Choromanski, David B. D'Ambrosio, Deepali Jain, Pannag Sanketi, Anish Shankar, Vikas Sindhwani, Sumeet Singh, Jean-Jacques E. Slotine, Stephen Tu
Agile Catching with Whole-Body MPC and Blackbox Policy Learning. CoRR (2023)
Sumeet Singh, Stephen Tu, Vikas Sindhwani
Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models. CoRR (2023)
Saminda Abeyruwan, Alex Bewley, Nicholas Matthew Boffi, Krzysztof Marcin Choromanski, David B. D'Ambrosio, Deepali Jain, Pannag R. Sanketi, Anish Shankar, Vikas Sindhwani, Sumeet Singh, Jean-Jacques E. Slotine, Stephen Tu
Agile Catching with Whole-Body MPC and Blackbox Policy Learning. L4DC (2023)
Simon Le Cleac'h, Mac Schwager, Zachary Manchester, Vikas Sindhwani, Pete Florence, Sumeet Singh
Single-Level Differentiable Contact Simulation. IEEE Robotics Autom. Lett. 8 (7) (2023)
David B. D'Ambrosio, Jonathan Abelian, Saminda Abeyruwan, Michael Ahn, Alex Bewley, Justin Boyd, Krzysztof Choromanski, Omar Cortes, Erwin Coumans, Tianli Ding, Wenbo Gao, Laura Graesser, Atil Iscen, Navdeep Jaitly, Deepali Jain, Juhana Kangaspunta, Satoshi Kataoka, Gus Kouretas, Yuheng Kuang, Nevena Lazic, Corey Lynch, Reza Mahjourian, Sherry Q. Moore, Thinh Nguyen, Ken Oslund, Barney J. Reed, Krista Reymann, Pannag R. Sanketi, Anish Shankar, Pierre Sermanet, Vikas Sindhwani, Avi Singh, Vincent Vanhoucke, Grace Vesom, Peng Xu
Robotic Table Tennis: A Case Study into a High Speed Learning System. CoRR (2023)
Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani, Stephen Tu
Safely Learning Dynamical Systems. CoRR (2023)
Andy Zeng, Maria Attarian, Brian Ichter, Krzysztof Marcin Choromanski, Adrian Wong, Stefan Welker, Federico Tombari, Aveek Purohit, Michael S. Ryoo, Vikas Sindhwani, Johnny Lee, Vincent Vanhoucke, Pete Florence
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language. ICLR (2023)
David B. D'Ambrosio, Navdeep Jaitly, Vikas Sindhwani, Ken Oslund, Peng Xu, Nevena Lazic, Anish Shankar, Tianli Ding, Jonathan Abelian, Erwin Coumans, Gus Kouretas, Thinh Nguyen, Justin Boyd, Atil Iscen, Reza Mahjourian, Vincent Vanhoucke, Alex Bewley, Yuheng Kuang, Michael Ahn, Deepali Jain, Satoshi Kataoka, Omar E. Cortes, Pierre Sermanet, Corey Lynch, Pannag R. Sanketi, Krzysztof Choromanski, Wenbo Gao, Juhana Kangaspunta, Krista Reymann, Grace Vesom, Sherry Q. Moore, Avi Singh, Saminda Wishwajith Abeyruwan, Laura Graesser
Robotic Table Tennis: A Case Study into a High Speed Learning System. Robotics: Science and Systems (2023)
Sohan Rudra, Saksham Goel, Anirban Santara, Claudio Gentile, Laurent Perron, Fei Xia, Vikas Sindhwani, Carolina Parada, Gaurav Aggarwal
A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations. ICRA (2023)
Taylor A. Howell, Simon Le Cleac'h, Sumeet Singh, Peter R. Florence, Zachary Manchester, Vikas Sindhwani
Trajectory Optimization with Optimization-Based Dynamics. IEEE Robotics Autom. Lett. 7 (3) (2022)
Xuesu Xiao, Tingnan Zhang, Krzysztof Choromanski, Tsang-Wei Edward Lee, Anthony G. Francis, Jake Varley, Stephen Tu, Sumeet Singh, Peng Xu, Fei Xia, Sven Mikael Persson, Dmitry Kalashnikov, Leila Takayama, Roy Frostig, Jie Tan, Carolina Parada, Vikas Sindhwani
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. CoRR (2022)
Sumeet Singh, Jean-Jacques E. Slotine, Vikas Sindhwani
Optimizing Trajectories with Closed-Loop Dynamic SQP. ICRA (2022)
Andy Zeng, Adrian Wong, Stefan Welker, Krzysztof Choromanski, Federico Tombari, Aveek Purohit, Michael S. Ryoo, Vikas Sindhwani, Johnny Lee, Vincent Vanhoucke, Pete Florence
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language. CoRR (2022)
Simon Le Cleac'h, Mac Schwager, Zachary Manchester, Vikas Sindhwani, Pete Florence, Sumeet Singh
Single-Level Differentiable Contact Simulation. CoRR (2022)
Xuesu Xiao, Tingnan Zhang, Krzysztof Marcin Choromanski, Tsang-Wei Edward Lee, Anthony G. Francis, Jake Varley, Stephen Tu, Sumeet Singh, Peng Xu, Fei Xia, Sven Mikael Persson, Dmitry Kalashnikov, Leila Takayama, Roy Frostig, Jie Tan, Carolina Parada, Vikas Sindhwani
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. CoRL (2022)
Yunfan Zhao, Qingkai Pan, Krzysztof Choromanski, Deepali Jain, Vikas Sindhwani
Implicit Two-Tower Policies. CoRR (2022)
Sohan Rudra, Saksham Goel, Anirban Santara, Claudio Gentile, Laurent Perron, Fei Xia, Vikas Sindhwani, Carolina Parada, Gaurav Aggarwal
A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations. CoRR (2022)
Sumeet Singh, Francis McCann Ramirez, Jacob Varley, Andy Zeng, Vikas Sindhwani
Multiscale Sensor Fusion and Continuous Control with Neural CDEs. CoRR (2022)
Sumeet Singh, Francis McCann Ramirez, Jacob Varley, Andy Zeng, Vikas Sindhwani
Multiscale Sensor Fusion and Continuous Control with Neural CDEs. IROS (2022)
Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael S. Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller
Hybrid Random Features. ICLR (2022)
Thomas Lew, Sumeet Singh, Mario Prats, Jeffrey Bingham, Jonathan Weisz, Benjie Holson, Xiaohan Zhang, Vikas Sindhwani, Yao Lu, Fei Xia, Peng Xu, Tingnan Zhang, Jie Tan, Montserrat Gonzalez
Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization. CoRR (2022)
Bachir El Khadir, Jean-Bernard Lasserre, Vikas Sindhwani
Piecewise-Linear Motion Planning amidst Static, Moving, or Morphing Obstacles. ICRA (2021)
Sumeet Singh, Spencer M. Richards, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
Learning stabilizable nonlinear dynamics with contraction-based regularization. Int. J. Robotics Res. 40 (10-11) (2021)
Taylor A. Howell, Simon Le Cleac'h, Sumeet Singh, Pete Florence, Zachary Manchester, Vikas Sindhwani
Trajectory Optimization with Optimization-Based Dynamics. CoRR (2021)
Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani, Stephen Tu
Safely Learning Dynamical Systems from Short Trajectories. L4DC (2021)
Krzysztof Choromanski, Haoxian Chen, Han Lin, Yuanzhe Ma, Arijit Sehanobish, Deepali Jain, Michael S. Ryoo, Jake Varley, Andy Zeng, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller
Hybrid Random Features. CoRR (2021)
Daniel Seita, Pete Florence, Jonathan Tompson, Erwin Coumans, Vikas Sindhwani, Ken Goldberg, Andy Zeng
Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks. ICRA (2021)
Malayandi Palan, Shane T. Barratt, Alex McCauley, Dorsa Sadigh, Vikas Sindhwani, Stephen P. Boyd
Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint. L4DC (2020)
Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, Johnny Lee
Transporter Networks: Rearranging the Visual World for Robotic Manipulation. CoRR (2020)
Daniel Seita, Pete Florence, Jonathan Tompson, Erwin Coumans, Vikas Sindhwani, Ken Goldberg, Andy Zeng
Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks. CoRR (2020)
Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, Johnny Lee
Transporter Networks: Rearranging the Visual World for Robotic Manipulation. CoRL (2020)
Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani, Stephen Tu
Safely Learning Dynamical Systems from Short Trajectories. CoRR (2020)
Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani
Learning Stability Certificates from Data. CoRL (2020)
Bachir El Khadir, Jean-Bernard Lasserre, Vikas Sindhwani
Piecewise-Linear Motion Planning amidst Static, Moving, or Morphing Obstacles. CoRR (2020)
Vikas Sindhwani, Hakim Sidahmed, Krzysztof Choromanski, Brandon Jones
Unsupervised Anomaly Detection for Self-flying Delivery Drones. ICRA (2020)
Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamás Sarlós, Adrian Weller, Vikas Sindhwani
Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML (2020)
Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song, Nevena Lazic, Pannag Sanketi, Vikas Sindhwani, Navdeep Jaitly
Robotic Table Tennis with Model-Free Reinforcement Learning. IROS (2020)
Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song, Nevena Lazic, Pannag Sanketi, Vikas Sindhwani, Navdeep Jaitly
Robotic Table Tennis with Model-Free Reinforcement Learning. CoRR (2020)
Jared Quincy Davis, Krzysztof Choromanski, Jake Varley, Honglak Lee, Jean-Jacques E. Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia, Vikas Sindhwani
Time Dependence in Non-Autonomous Neural ODEs. CoRR (2020)
Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani
Learning Stability Certificates from Data. CoRR (2020)
Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
Ode to an ODE. NeurIPS (2020)
Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamás Sarlós, Adrian Weller, Vikas Sindhwani
Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR (2020)
Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
An Ode to an ODE. CoRR (2020)
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Jasmine Hsu, Atil Iscen, Deepali Jain, Vikas Sindhwani
When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies. CoRR (2019)
Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Tingnan Zhang, Jie Tan, Vikas Sindhwani
Data Efficient Reinforcement Learning for Legged Robots. CoRL (2019)
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Deepali Jain, Yuxiang Yang, Atil Iscen, Jasmine Hsu, Vikas Sindhwani
Provably Robust Blackbox Optimization for Reinforcement Learning. CoRL (2019)
Atil Iscen, Ken Caluwaerts, Jie Tan, Tingnan Zhang, Erwin Coumans, Vikas Sindhwani, Vincent Vanhoucke
Policies Modulating Trajectory Generators. CoRR (2019)
Bachir El Khadir, Jacob Varley, Vikas Sindhwani
Teleoperator Imitation with Continuous-Time Safety. Robotics: Science and Systems (2019)
Bachir El Khadir, Jake Varley, Vikas Sindhwani
Teleoperator Imitation with Continuous-time Safety. CoRR (2019)
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Vikas Sindhwani
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization. NeurIPS (2019)
Sumeet Singh, Spencer M. Richards, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization. CoRR (2019)
Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Tingnan Zhang, Jie Tan, Vikas Sindhwani
Data Efficient Reinforcement Learning for Legged Robots. CoRR (2019)
Krzysztof Choromanski, Atil Iscen, Vikas Sindhwani, Jie Tan, Erwin Coumans
Optimizing Simulations with Noise-Tolerant Structured Exploration. ICRA (2018)
Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller
The Geometry of Random Features. AISTATS (2018)
Krzysztof Choromanski, Vikas Sindhwani, Brandon Jones, Damien Jourdan, Maciej Chociej, Byron Boots
Learning-based Air Data System for Safe and Efficient Control of Fixed-wing Aerial Vehicles. SSRR (2018)
Krzysztof Choromanski, Atil Iscen, Vikas Sindhwani, Jie Tan, Erwin Coumans
Optimizing Simulations with Noise-Tolerant Structured Exploration. CoRR (2018)
Sumeet Singh, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
Learning Stabilizable Dynamical Systems via Control Contraction Metrics. WAFR (2018)
Atil Iscen, Ken Caluwaerts, Jie Tan, Tingnan Zhang, Erwin Coumans, Vikas Sindhwani, Vincent Vanhoucke
Policies Modulating Trajectory Generators. CoRL (2018)
Vikas Sindhwani, Stephen Tu, Mohi Khansari
Learning Contracting Vector Fields For Stable Imitation Learning. CoRR (2018)
Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller
Structured Evolution with Compact Architectures for Scalable Policy Optimization. CoRR (2018)
Sumeet Singh, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
Learning Stabilizable Dynamical Systems via Control Contraction Metrics. CoRR (2018)
Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller
Structured Evolution with Compact Architectures for Scalable Policy Optimization. ICML (2018)
Krzysztof Marcin Choromanski, Vikas Sindhwani
On Blackbox Backpropagation and Jacobian Sensing. NIPS (2017)
Jie Chen, Haim Avron, Vikas Sindhwani
Hierarchically Compositional Kernels for Scalable Nonparametric Learning. J. Mach. Learn. Res. 18 (2017)
Amir Ali Ahmadi, Georgina Hall, Ameesh Makadia, Vikas Sindhwani
Geometry of 3D Environments and Sum of Squares Polynomials. Robotics: Science and Systems (2017)
Xinyan Yan, Krzysztof Choromanski, Byron Boots, Vikas Sindhwani
Manifold Regularization for Kernelized LSTD. CoRR (2017)
Vikas Sindhwani, Rebecca Roelofs, Mrinal Kalakrishnan
Sequential operator splitting for constrained nonlinear optimal control. ACC (2017)
Jie Chen, Haim Avron, Vikas Sindhwani
Hierarchically Compositional Kernels for Scalable Nonparametric Learning. CoRR (2016)
Krzysztof Choromanski, Vikas Sindhwani
Recycling Randomness with Structure for Sublinear time Kernel Expansions. ICML (2016)
Krzysztof Choromanski, Vikas Sindhwani
Recycling Randomness with Structure for Sublinear time Kernel Expansions. CoRR (2016)
Amir Ali Ahmadi, Georgina Hall, Ameesh Makadia, Vikas Sindhwani
Geometry of 3D Environments and Sum of Squares Polynomials. CoRR (2016)
Haim Avron, Vikas Sindhwani, Jiyan Yang, Michael W. Mahoney
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. J. Mach. Learn. Res. 17 (2016)
Zhiyun Lu, Vikas Sindhwani, Tara N. Sainath
Learning compact recurrent neural networks. ICASSP (2016)
Haim Avron, Vikas Sindhwani
High-Performance Kernel Machines With Implicit Distributed Optimization and Randomization. Technometrics 58 (3) (2016)
Zhiyun Lu, Vikas Sindhwani, Tara N. Sainath
Learning Compact Recurrent Neural Networks. CoRR (2016)
Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
Structured Transforms for Small-Footprint Deep Learning. CoRR (2015)
Abhishek Kumar, Vikas Sindhwani
and Bregman Loss Functions. SDM (2015)
Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
Structured Transforms for Small-Footprint Deep Learning. NIPS (2015)
Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael W. Mahoney
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. ICML (2014)
Po-Sen Huang, Haim Avron, Tara N. Sainath, Vikas Sindhwani, Bhuvana Ramabhadran
Kernel methods match Deep Neural Networks on TIMIT. ICASSP (2014)
Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael W. Mahoney
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. CoRR (2014)
Vikas Sindhwani, Ha Quang Minh, Aurelie C. Lozano
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. CoRR (2014)
Ramakrishna B. Bairi, Ganesh Ramakrishnan, Vikas Sindhwani
Personalized classifiers: evolving a classifier from a large reference knowledge graph. IDEAS (2014)
Suyog Gupta, Vikas Sindhwani, Kailash Gopalakrishnan
Learning Machines Implemented on Non-Deterministic Hardware. CoRR (2014)
Jiyan Yang, Vikas Sindhwani, Quanfu Fan, Haim Avron, Michael W. Mahoney
Random Laplace Feature Maps for Semigroup Kernels on Histograms. CVPR (2014)
Vikas Sindhwani, Haim Avron
High-performance Kernel Machines with Implicit Distributed Optimization and Randomization. CoRR (2014)
Abhishek Kumar, Vikas Sindhwani
- and Bregman Loss Functions. CoRR (2013)
Vikas Sindhwani, Ha Quang Minh, Aurelie C. Lozano
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. UAI (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Vikas Sindhwani