Vikas Sindhwani

156 papers A* 36A 12C 3Misc 11Journal 70Unranked 21

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Achieving Human Level Competitive Robot Table Tennis. ICRA David B. D'Ambrosio, Saminda Abeyruwan, Laura Graesser, Atil Iscen, Heni Ben Amor, Alex Bewley, Barney J. Reed, Krista Reymann, Leila Takayama, Yuval Tassa, Krzysztof Choromanski, Erwin Coumans, Deepali Jain, Navdeep Jaitly, Natasha Jaques, Satoshi Kataoka, Yuheng Kuang, Nevena Lazic, Reza Mahjourian, Sherry Moore, Kenneth Oslund, Anish Shankar, Vikas Sindhwani, Vincent Vanhoucke, Grace Vesom, Peng Xu, Pannag R. Sanketi
2025	J	`jnl`	Can AI Perceive Physical Danger and Intervene? CoRR Abhishek Jindal, Dmitry Kalashnikov, Oscar Chang, Divya Garikapati, Anirudha Majumdar, Pierre Sermanet, Vikas Sindhwani
2025	J	`jnl`	Generating Robot Constitutions & Benchmarks for Semantic Safety. CoRR Pierre Sermanet, Anirudha Majumdar, Alex Irpan, Dmitry Kalashnikov, Vikas Sindhwani
2025	A*	`conf`	Learning the RoPEs: Better 2D and 3D Position Encodings with STRING. ICML Connor Schenck, Isaac Reid, Mithun George Jacob, Alex Bewley, Joshua Ainslie, David Rendleman, Deepali Jain, Mohit Sharma, Kumar Avinava Dubey, Ayzaan Wahid, Sumeet Singh, René Wagner, Tianli Ding, Chuyuan Fu, Arunkumar Byravan, Jake Varley, Alexey A. Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, Krzysztof Marcin Choromanski
2025	J	`jnl`	Learning the RoPEs: Better 2D and 3D Position Encodings with STRING. CoRR Connor Schenck, Isaac Reid, Mithun George Jacob, Alex Bewley, Joshua Ainslie, David Rendleman, Deepali Jain, Mohit Sharma, Avinava Dubey, Ayzaan Wahid, Sumeet Singh, René Wagner, Tianli Ding, Chuyuan Fu, Arunkumar Byravan, Jake Varley, Alexey A. Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, Krzysztof Choromanski
2025	J	`jnl`	Predictive Red Teaming: Breaking Policies Without Breaking Robots. CoRR Anirudha Majumdar, Mohit Sharma, Dmitry Kalashnikov, Sumeet Singh, Pierre Sermanet, Vikas Sindhwani
2025	J	`jnl`	SciFi-Benchmark: How Would AI-Powered Robots Behave in Science Fiction Literature? CoRR Pierre Sermanet, Anirudha Majumdar, Vikas Sindhwani
2024	J	`jnl`	Achieving Human Level Competitive Robot Table Tennis. CoRR David B. D'Ambrosio, Saminda Abeyruwan, Laura Graesser, Atil Iscen, Heni Ben Amor, Alex Bewley, Barney J. Reed, Krista Reymann, Leila Takayama, Yuval Tassa, Krzysztof Choromanski, Erwin Coumans, Deepali Jain, Navdeep Jaitly, Natasha Jaques, Satoshi Kataoka, Yuheng Kuang, Nevena Lazic, Reza Mahjourian, Sherry Moore, Kenneth Oslund, Anish Shankar, Vikas Sindhwani, Vincent Vanhoucke, Grace Vesom, Peng Xu, Pannag R. Sanketi
2024	A	`conf`	Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity. IROS Jake Varley, Sumeet Singh, Deepali Jain, Krzysztof Choromanski, Andy Zeng, Somnath Basu Roy Chowdhury, Avinava Dubey, Vikas Sindhwani
2024	J	`jnl`	Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity. CoRR Jake Varley, Sumeet Singh, Deepali Jain, Krzysztof Choromanski, Andy Zeng, Somnath Basu Roy Chowdhury, Avinava Dubey, Vikas Sindhwani
2024	A*	`conf`	How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies. ICRA 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
2024	Misc	`conf`	Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. CoRL Zhuo Xu, Hao-Tien Lewis Chiang, 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
2024	J	`jnl`	Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs. CoRR 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
2024	Misc	`conf`	Modeling the Real World with High-Density Visual Particle Dynamics. CoRL William F. Whitney, Jake Varley, Deepali Jain, Krzysztof Marcin Choromanski, Sumeet Singh, Vikas Sindhwani
2024	J	`jnl`	Modeling the Real World with High-Density Visual Particle Dynamics. CoRR William F. Whitney, Jacob Varley, Deepali Jain, Krzysztof Choromanski, Sumeet Singh, Vikas Sindhwani
2024	J	`jnl`	Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models. Trans. Mach. Learn. Res. Sumeet Singh, Stephen Tu, Vikas Sindhwani
2024	A*	`conf`	SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. ICRA 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
2024	J	`jnl`	Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning. CoRR Arijit Sehanobish, Avinava Dubey, Krzysztof Choromanski, Somnath Basu Roy Chowdhury, Deepali Jain, Vikas Sindhwani, Snigdha Chaturvedi
2024	A*	`conf`	Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning. NeurIPS Arijit Sehanobish, Kumar Avinava Dubey, Krzysztof Marcin Choromanski, Somnath Basu Roy Chowdhury, Deepali Jain, Vikas Sindhwani, Snigdha Chaturvedi
2024	A	`conf`	The Design of the Barkour Benchmark for Robot Agility. IROS Wenhao Yu, Ken Caluwaerts, Atil Iscen, J. Chase Kew, Tingnan Zhang, Daniel Freeman, Lisa Lee, Stefano Saliceti, Vincent Zhuang, Nathan Batchelor, Steven Bohez, Federico Casarini, José Enrique Chen, Erwin Coumans, Adil Dostmohamed, Gabriel Dulac-Arnold, Alejandro Escontrela, Erik Frey, Roland Hafner, Deepali Jain, Bauyrjan Jyenis, Yuheng Kuang, Tsang-Wei Edward Lee, Ofir Nachum, Ken Oslund, Francesco Romano, Fereshteh Sadeghi, Baruch Tabanpour, Daniel Zheng, Michael Neunert, Raia Hadsell, Nicolas Heess, Francesco Nori, Jeff Seto, Carolina Parada, Vikas Sindhwani, Vincent Vanhoucke, Jie Tan, Kuang-Huei Lee
2023	A*	`conf`	A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations. ICRA Sohan Rudra, Saksham Goel, Anirban Santara, Claudio Gentile, Laurent Perron, Fei Xia, Vikas Sindhwani, Carolina Parada, Gaurav Aggarwal
2023	—	`conf`	Agile Catching with Whole-Body MPC and Blackbox Policy Learning. L4DC 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
2023	J	`jnl`	Agile Catching with Whole-Body MPC and Blackbox Policy Learning. CoRR 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
2023	J	`jnl`	Barkour: Benchmarking Animal-level Agility with Quadruped Robots. CoRR 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, José 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
2023	—	`conf`	Demonstrating Large Language Models on Robots. Robotics: Science and Systems Andy Zeng, Brian Ichter, Fei Xia, Ted Xiao, Vikas Sindhwani
2023	A*	`conf`	Mnemosyne: Learning to Train Transformers with Transformers. NeurIPS Deepali Jain, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan
2023	J	`jnl`	Mnemosyne: Learning to Train Transformers with Transformers. CoRR Deepali Jain, Krzysztof Marcin Choromanski, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan, Avinava Dubey
2023	J	`jnl`	Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models. CoRR Sumeet Singh, Stephen Tu, Vikas Sindhwani
2023	—	`conf`	Robotic Table Tennis: A Case Study into a High Speed Learning System. Robotics: Science and Systems 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
2023	J	`jnl`	Robotic Table Tennis: A Case Study into a High Speed Learning System. CoRR 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
2023	A*	`conf`	Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization. ICRA Thomas Lew, Sumeet Singh, Mario Prats, Jeffrey T. Bingham, Jonathan Weisz, Benjie Holson, Xiaohan Zhang, Vikas Sindhwani, Yao Lu, Fei Xia, Peng Xu, Tingnan Zhang, Jie Tan, Montserrat Gonzalez
2023	J	`jnl`	SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. CoRR 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
2023	J	`jnl`	Safely Learning Dynamical Systems. CoRR Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani, Stephen Tu
2023	J	`jnl`	Single-Level Differentiable Contact Simulation. IEEE Robotics Autom. Lett. Simon Le Cleac'h, Mac Schwager, Zachary Manchester, Vikas Sindhwani, Pete Florence, Sumeet Singh
2023	A*	`conf`	Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language. ICLR 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
2022	J	`jnl`	A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations. CoRR Sohan Rudra, Saksham Goel, Anirban Santara, Claudio Gentile, Laurent Perron, Fei Xia, Vikas Sindhwani, Carolina Parada, Gaurav Aggarwal
2022	A*	`conf`	Hybrid Random Features. ICLR 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
2022	J	`jnl`	Implicit Two-Tower Policies. CoRR Yunfan Zhao, Qingkai Pan, Krzysztof Choromanski, Deepali Jain, Vikas Sindhwani
2022	Misc	`conf`	Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. CoRL 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
2022	J	`jnl`	Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. CoRR 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
2022	A	`conf`	Multiscale Sensor Fusion and Continuous Control with Neural CDEs. IROS Sumeet Singh, Francis McCann Ramirez, Jacob Varley, Andy Zeng, Vikas Sindhwani
2022	J	`jnl`	Multiscale Sensor Fusion and Continuous Control with Neural CDEs. CoRR Sumeet Singh, Francis McCann Ramirez, Jacob Varley, Andy Zeng, Vikas Sindhwani
2022	A*	`conf`	Optimizing Trajectories with Closed-Loop Dynamic SQP. ICRA Sumeet Singh, Jean-Jacques E. Slotine, Vikas Sindhwani
2022	J	`jnl`	Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization. CoRR Thomas Lew, Sumeet Singh, Mario Prats, Jeffrey T. Bingham, Jonathan Weisz, Benjie Holson, Xiaohan Zhang, Vikas Sindhwani, Yao Lu, Fei Xia, Peng Xu, Tingnan Zhang, Jie Tan, Montserrat Gonzalez
2022	J	`jnl`	Single-Level Differentiable Contact Simulation. CoRR Simon Le Cleac'h, Mac Schwager, Zachary Manchester, Vikas Sindhwani, Pete Florence, Sumeet Singh
2022	J	`jnl`	Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language. CoRR Andy Zeng, Adrian Wong, Stefan Welker, Krzysztof Choromanski, Federico Tombari, Aveek Purohit, Michael S. Ryoo, Vikas Sindhwani, Johnny Lee, Vincent Vanhoucke, Pete Florence
2022	J	`jnl`	Trajectory Optimization with Optimization-Based Dynamics. IEEE Robotics Autom. Lett. Taylor A. Howell, Simon Le Cleac'h, Sumeet Singh, Peter R. Florence, Zachary Manchester, Vikas Sindhwani
2021	J	`jnl`	Hybrid Random Features. CoRR 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
2021	J	`jnl`	Learning stabilizable nonlinear dynamics with contraction-based regularization. Int. J. Robotics Res. Sumeet Singh, Spencer M. Richards, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
2021	A*	`conf`	Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks. ICRA Daniel Seita, Pete Florence, Jonathan Tompson, Erwin Coumans, Vikas Sindhwani, Ken Goldberg, Andy Zeng
2021	A*	`conf`	Piecewise-Linear Motion Planning amidst Static, Moving, or Morphing Obstacles. ICRA Bachir El Khadir, Jean-Bernard Lasserre, Vikas Sindhwani
2021	—	`conf`	Safely Learning Dynamical Systems from Short Trajectories. L4DC Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani, Stephen Tu
2021	J	`jnl`	Trajectory Optimization with Optimization-Based Dynamics. CoRR Taylor A. Howell, Simon Le Cleac'h, Sumeet Singh, Pete Florence, Zachary Manchester, Vikas Sindhwani
2020	J	`jnl`	An Ode to an ODE. CoRR Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
2020	—	`conf`	Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint. L4DC Malayandi Palan, Shane T. Barratt, Alex McCauley, Dorsa Sadigh, Vikas Sindhwani, Stephen P. Boyd
2020	Misc	`conf`	Learning Stability Certificates from Data. CoRL Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani
2020	J	`jnl`	Learning Stability Certificates from Data. CoRR Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani
2020	J	`jnl`	Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks. CoRR Daniel Seita, Pete Florence, Jonathan Tompson, Erwin Coumans, Vikas Sindhwani, Ken Goldberg, Andy Zeng
2020	A*	`conf`	Ode to an ODE. NeurIPS Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
2020	J	`jnl`	Piecewise-Linear Motion Planning amidst Static, Moving, or Morphing Obstacles. CoRR Bachir El Khadir, Jean-Bernard Lasserre, Vikas Sindhwani
2020	A	`conf`	Robotic Table Tennis with Model-Free Reinforcement Learning. IROS Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song, Nevena Lazic, Pannag Sanketi, Vikas Sindhwani, Navdeep Jaitly
2020	J	`jnl`	Robotic Table Tennis with Model-Free Reinforcement Learning. CoRR Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song, Nevena Lazic, Pannag Sanketi, Vikas Sindhwani, Navdeep Jaitly
2020	J	`jnl`	Safely Learning Dynamical Systems from Short Trajectories. CoRR Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani, Stephen Tu
2020	A*	`conf`	Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML 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
2020	J	`jnl`	Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR 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
2020	J	`jnl`	Time Dependence in Non-Autonomous Neural ODEs. CoRR Jared Quincy Davis, Krzysztof Choromanski, Jake Varley, Honglak Lee, Jean-Jacques E. Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia, Vikas Sindhwani
2020	Misc	`conf`	Transporter Networks: Rearranging the Visual World for Robotic Manipulation. CoRL Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, Johnny Lee
2020	J	`jnl`	Transporter Networks: Rearranging the Visual World for Robotic Manipulation. CoRR Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, Johnny Lee
2020	A*	`conf`	Unsupervised Anomaly Detection for Self-flying Delivery Drones. ICRA Vikas Sindhwani, Hakim Sidahmed, Krzysztof Choromanski, Brandon Jones
2019	Misc	`conf`	Data Efficient Reinforcement Learning for Legged Robots. CoRL Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Tingnan Zhang, Jie Tan, Vikas Sindhwani
2019	J	`jnl`	Data Efficient Reinforcement Learning for Legged Robots. CoRR Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Tingnan Zhang, Jie Tan, Vikas Sindhwani
2019	A*	`conf`	From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization. NeurIPS Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Vikas Sindhwani
2019	J	`jnl`	Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization. CoRR Sumeet Singh, Spencer M. Richards, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
2019	J	`jnl`	Policies Modulating Trajectory Generators. CoRR Atil Iscen, Ken Caluwaerts, Jie Tan, Tingnan Zhang, Erwin Coumans, Vikas Sindhwani, Vincent Vanhoucke
2019	Misc	`conf`	Provably Robust Blackbox Optimization for Reinforcement Learning. CoRL Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Deepali Jain, Yuxiang Yang, Atil Iscen, Jasmine Hsu, Vikas Sindhwani
2019	—	`conf`	Teleoperator Imitation with Continuous-Time Safety. Robotics: Science and Systems Bachir El Khadir, Jacob Varley, Vikas Sindhwani
2019	J	`jnl`	Teleoperator Imitation with Continuous-time Safety. CoRR Bachir El Khadir, Jake Varley, Vikas Sindhwani
2019	J	`jnl`	When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies. CoRR Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Jasmine Hsu, Atil Iscen, Deepali Jain, Vikas Sindhwani
2018	J	`jnl`	Learning Contracting Vector Fields For Stable Imitation Learning. CoRR Vikas Sindhwani, Stephen Tu, Mohi Khansari
2018	C	`conf`	Learning Stabilizable Dynamical Systems via Control Contraction Metrics. WAFR Sumeet Singh, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
2018	J	`jnl`	Learning Stabilizable Dynamical Systems via Control Contraction Metrics. CoRR Sumeet Singh, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
2018	—	`conf`	Learning-based Air Data System for Safe and Efficient Control of Fixed-wing Aerial Vehicles. SSRR Krzysztof Choromanski, Vikas Sindhwani, Brandon Jones, Damien Jourdan, Maciej Chociej, Byron Boots
2018	A*	`conf`	Optimizing Simulations with Noise-Tolerant Structured Exploration. ICRA Krzysztof Choromanski, Atil Iscen, Vikas Sindhwani, Jie Tan, Erwin Coumans
2018	J	`jnl`	Optimizing Simulations with Noise-Tolerant Structured Exploration. CoRR Krzysztof Choromanski, Atil Iscen, Vikas Sindhwani, Jie Tan, Erwin Coumans
2018	Misc	`conf`	Policies Modulating Trajectory Generators. CoRL Atil Iscen, Ken Caluwaerts, Jie Tan, Tingnan Zhang, Erwin Coumans, Vikas Sindhwani, Vincent Vanhoucke
2018	A*	`conf`	Structured Evolution with Compact Architectures for Scalable Policy Optimization. ICML Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller
2018	J	`jnl`	Structured Evolution with Compact Architectures for Scalable Policy Optimization. CoRR Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller
2018	A	`conf`	The Geometry of Random Features. AISTATS Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller
2017	—	`conf`	Geometry of 3D Environments and Sum of Squares Polynomials. Robotics: Science and Systems Amir Ali Ahmadi, Georgina Hall, Ameesh Makadia, Vikas Sindhwani
2017	J	`jnl`	Hierarchically Compositional Kernels for Scalable Nonparametric Learning. J. Mach. Learn. Res. Jie Chen, Haim Avron, Vikas Sindhwani
2017	J	`jnl`	Manifold Regularization for Kernelized LSTD. CoRR Xinyan Yan, Krzysztof Choromanski, Byron Boots, Vikas Sindhwani
2017	—	`conf`	On Blackbox Backpropagation and Jacobian Sensing. NIPS Krzysztof Marcin Choromanski, Vikas Sindhwani
2017	—	`ch.`	Recommender Systems. Encyclopedia of Machine Learning and Data Mining Prem Melville, Vikas Sindhwani
2017	C	`conf`	Sequential operator splitting for constrained nonlinear optimal control. ACC Vikas Sindhwani, Rebecca Roelofs, Mrinal Kalakrishnan
2016	J	`jnl`	Geometry of 3D Environments and Sum of Squares Polynomials. CoRR Amir Ali Ahmadi, Georgina Hall, Ameesh Makadia, Vikas Sindhwani
2016	J	`jnl`	Hierarchically Compositional Kernels for Scalable Nonparametric Learning. CoRR Jie Chen, Haim Avron, Vikas Sindhwani
2016	J	`jnl`	High-Performance Kernel Machines With Implicit Distributed Optimization and Randomization. Technometrics Haim Avron, Vikas Sindhwani
2016	J	`jnl`	Learning Compact Recurrent Neural Networks. CoRR Zhiyun Lu, Vikas Sindhwani, Tara N. Sainath
2016	Misc	`conf`	Learning compact recurrent neural networks. ICASSP Zhiyun Lu, Vikas Sindhwani, Tara N. Sainath
2016	J	`jnl`	Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. J. Mach. Learn. Res. Haim Avron, Vikas Sindhwani, Jiyan Yang, Michael W. Mahoney
2016	A*	`conf`	Recycling Randomness with Structure for Sublinear time Kernel Expansions. ICML Krzysztof Choromanski, Vikas Sindhwani
2016	J	`jnl`	Recycling Randomness with Structure for Sublinear time Kernel Expansions. CoRR Krzysztof Choromanski, Vikas Sindhwani
2015	A	`conf`	Near-separable Non-negative Matrix Factorization with ℓ SDM Abhishek Kumar, Vikas Sindhwani
2015	—	`conf`	Structured Transforms for Small-Footprint Deep Learning. NIPS Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
2015	J	`jnl`	Structured Transforms for Small-Footprint Deep Learning. CoRR Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
2014	J	`jnl`	High-performance Kernel Machines with Implicit Distributed Optimization and Randomization. CoRR Vikas Sindhwani, Haim Avron
2014	Misc	`conf`	Kernel methods match Deep Neural Networks on TIMIT. ICASSP Po-Sen Huang, Haim Avron, Tara N. Sainath, Vikas Sindhwani, Bhuvana Ramabhadran
2014	J	`jnl`	Learning Machines Implemented on Non-Deterministic Hardware. CoRR Suyog Gupta, Vikas Sindhwani, Kailash Gopalakrishnan
2014	C	`conf`	Personalized classifiers: evolving a classifier from a large reference knowledge graph. IDEAS Ramakrishna B. Bairi, Ganesh Ramakrishnan, Vikas Sindhwani
2014	A*	`conf`	Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. ICML Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael W. Mahoney
2014	J	`jnl`	Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. CoRR Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael W. Mahoney
2014	A*	`conf`	Random Laplace Feature Maps for Semigroup Kernels on Histograms. CVPR Jiyan Yang, Vikas Sindhwani, Quanfu Fan, Haim Avron, Michael W. Mahoney
2014	J	`jnl`	Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. CoRR Vikas Sindhwani, Ha Quang Minh, Aurélie C. Lozano
2013	—	`conf`	Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization. ICML (1) Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur
2013	Misc	`conf`	Low-rank matrix factorization for Deep Neural Network training with high-dimensional output targets. ICASSP Tara N. Sainath, Brian Kingsbury, Vikas Sindhwani, Ebru Arisoy, Bhuvana Ramabhadran
2013	J	`jnl`	Near-separable Non-negative Matrix Factorization with ℓ CoRR Abhishek Kumar, Vikas Sindhwani
2013	A	`conf`	Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. UAI Vikas Sindhwani, Ha Quang Minh, Aurélie C. Lozano
2013	—	`conf`	Sketching Structured Matrices for Faster Nonlinear Regression. NIPS Haim Avron, Vikas Sindhwani, David P. Woodruff
2012	A*	`conf`	Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization. ICML Haim Avron, Satyen Kale, Shiva Prasad Kasiviswanathan, Vikas Sindhwani
2012	J	`jnl`	Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization CoRR Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur
2012	A*	`conf`	Large-scale distributed non-negative sparse coding and sparse dictionary learning. KDD Vikas Sindhwani, Amol Ghoting
2012	A	`conf`	Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization. WSDM Ankan Saha, Vikas Sindhwani
2012	J	`jnl`	Scalable Matrix-valued Kernel Learning and High-dimensional Nonlinear Causal Inference CoRR Vikas Sindhwani, Aurélie C. Lozano, Ha Quang Minh
2011	A*	`conf`	Concept Labeling: Building Text Classifiers with Minimal Supervision. IJCAI Vijil Chenthamarakshan, Prem Melville, Vikas Sindhwani, Richard D. Lawrence
2011	A	`conf`	Emerging topic detection using dictionary learning. CIKM Shiva Prasad Kasiviswanathan, Prem Melville, Arindam Banerjee, Vikas Sindhwani
2011	J	`jnl`	Extracting insights from social media with large-scale matrix approximations. IBM J. Res. Dev. Vikas Sindhwani, Amol Ghoting, Edison Ting, Richard D. Lawrence
2011	—	`conf`	Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels. NIPS Vikas Sindhwani, Aurélie C. Lozano
2011	A*	`conf`	SystemML: Declarative machine learning on MapReduce. ICDE Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D. Pednault, Berthold Reinwald, Vikas Sindhwani, Shirish Tatikonda, Yuanyuan Tian, Shivakumar Vaithyanathan
2011	A*	`conf`	Vector-valued Manifold Regularization. ICML Ha Quang Minh, Vikas Sindhwani
2010	—	`conf`	Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference. NIPS Aurélie C. Lozano, Vikas Sindhwani
2010	A	`conf`	Bridging Domains with Words: Opinion Analysis with Matrix Tri-factorizations. SDM Tao Li, Vikas Sindhwani, Chris H. Q. Ding, Yi Zhang
2010	A*	`conf`	One-Class Matrix Completion with Low-Density Factorizations. ICDM Vikas Sindhwani, Serhat Selcuk Bucak, Jianying Hu, Aleksandra Mojsilovic
2010	—	`ch.`	Recommender Systems. Encyclopedia of Machine Learning Prem Melville, Vikas Sindhwani
2009	—	`conf`	A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge. ACL/IJCNLP Tao Li, Yi Zhang, Vikas Sindhwani
2009	A*	`conf`	Knowledge transformation for cross-domain sentiment classification. SIGIR Tao Li, Vikas Sindhwani, Chris H. Q. Ding, Yi Zhang
2009	J	`jnl`	Leveraging social networks for corporate staffing and expert recommendation. IBM J. Res. Dev. Vijil Chenthamarakshan, Kuntal Dey, Jianying Hu, Aleksandra Mojsilovic, W. Riddle, Vikas Sindhwani
2009	J	`jnl`	Multiview point cloud kernels for semisupervised learning [Lecture Notes]. IEEE Signal Process. Mag. David S. Rosenberg, Vikas Sindhwani, Peter L. Bartlett, Partha Niyogi
2009	—	`conf`	Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework. ICDM Workshops Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikonda
2009	A*	`conf`	Uncertainty sampling and transductive experimental design for active dual supervision. ICML Vikas Sindhwani, Prem Melville, Richard D. Lawrence
2009	—	`conf`	Winning the KDD Cup Orange Challenge with Ensemble Selection. KDD Cup Alexandru Niculescu-Mizil, Claudia Perlich, Grzegorz Swirszcz, Vikas Sindhwani, Yan Liu, Prem Melville, Dong Wang, Jing Xiao, Jianying Hu, Moninder Singh, Wei Xiong Shang, Yanfeng Zhu
2008	A*	`conf`	An RKHS for multi-view learning and manifold co-regularization. ICML Vikas Sindhwani, David S. Rosenberg
2008	A*	`conf`	Document-Word Co-regularization for Semi-supervised Sentiment Analysis. ICDM Vikas Sindhwani, Prem Melville
2008	J	`jnl`	Optimization Techniques for Semi-Supervised Support Vector Machines. J. Mach. Learn. Res. Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi
2008	—	`conf`	Regularized Co-Clustering with Dual Supervision. NIPS Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovic
2007	A*	`conf`	Semi-Supervised Gaussian Process Classifiers. IJCAI Vikas Sindhwani, Wei Chu, S. Sathiya Keerthi
2006	—	`conf`	An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models. NIPS S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle
2006	—	`conf`	Branch and Bound for Semi-Supervised Support Vector Machines. NIPS Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi
2006	A*	`conf`	Deterministic annealing for semi-supervised kernel machines. ICML Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle
2006	A*	`conf`	Large scale semi-supervised linear SVMs. SIGIR Vikas Sindhwani, S. Sathiya Keerthi
2006	J	`jnl`	Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples. J. Mach. Learn. Res. Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
2006	—	`conf`	Relational Learning with Gaussian Processes. NIPS Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. Sathiya Keerthi
2006	—	`ch.`	The Geometric Basis of Semi-Supervised Learning. Semi-Supervised Learning Vikas Sindhwani, Misha Belkin, Partha Niyogi
2005	A*	`conf`	Beyond the point cloud: from transductive to semi-supervised learning. ICML Vikas Sindhwani, Partha Niyogi, Mikhail Belkin
2005	A	`conf`	On Manifold Regularization. AISTATS Misha Belkin, Partha Niyogi, Vikas Sindhwani
2004	J	`jnl`	Feature selection in MLPs and SVMs based on maximum output information. IEEE Trans. Neural Networks Vikas Sindhwani, Subrata Rakshit, Dipti Deodhare, Deniz Erdogmus, José Carlos Príncipe, Partha Niyogi
2001	A	`conf`	Information Theoretic Feature Crediting in Multiclass Support Vector Machines. SDM Vikas Sindhwani, P. Bhattacharya, Subrata Rakshit