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Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
September 6, 2021
Physarum Powered Differentiable Linear Programming Layers and Applications
Zihang Meng, Sathya N Ravi, Vikas Singh
Advances in Neural Information Processing Systems
|
April 7, 2022
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs
Zihang Meng, Lopamudra Mukherjee, Yichao Wu, et al.
Proceedings of Machine Learning Research
|
June 17, 2024
Controlled Differential Equations on Long Sequences via Non-standard Wavelets
Sourav Pal, Zhanpeng Zeng, Sathya N Ravi, et al.
Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
|
July 13, 2023
Deep Unlearning via Randomized Conditionally Independent Hessians
Ronak Mehta, Sourav Pal, Vikas Singh, et al.
Advances in Neural Information Processing Systems
|
June 24, 2022
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
Zihang Meng, Rudrasis Chakraborty, Vikas Singh
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
June 7, 2021
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains
Sathya N Ravi, Abhay Venkatesh, Glenn M Fung, et al.
Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
|
October 21, 2022
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets
Vishnu Suresh Lokhande, Sathya N Ravi, Rudrasis Chakraborty, et al.
Uncertainty in Artificial Intelligence : Proceedings of the ... Conference. Conference on Uncertainty in Artificial Intelligence
|
October 11, 2021
A Variational Approximation for Analyzing the Dynamics of Panel Data
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, et al.
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
August 18, 2021
Learning Invariant Representations using Inverse Contrastive Loss
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N Ravi, et al.
JMLR Workshop and Conference Proceedings
|
May 9, 2017
Experimental Design on a Budget for Sparse Linear Models and Applications
Sathya N Ravi, Vamsi K Ithapu, Sterling C Johnson, et al.
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Showing results (1-10 of 413) with videos related to
Sort By:
Page
of 42
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
September 6, 2021
Physarum Powered Differentiable Linear Programming Layers and Applications
Zihang Meng, Sathya N Ravi, Vikas Singh
Advances in Neural Information Processing Systems
|
April 7, 2022
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs
Zihang Meng, Lopamudra Mukherjee, Yichao Wu, et al.
Proceedings of Machine Learning Research
|
June 17, 2024
Controlled Differential Equations on Long Sequences via Non-standard Wavelets
Sourav Pal, Zhanpeng Zeng, Sathya N Ravi, et al.
Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
|
July 13, 2023
Deep Unlearning via Randomized Conditionally Independent Hessians
Ronak Mehta, Sourav Pal, Vikas Singh, et al.
Advances in Neural Information Processing Systems
|
June 24, 2022
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
Zihang Meng, Rudrasis Chakraborty, Vikas Singh
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
June 7, 2021
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains
Sathya N Ravi, Abhay Venkatesh, Glenn M Fung, et al.
Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
|
October 21, 2022
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets
Vishnu Suresh Lokhande, Sathya N Ravi, Rudrasis Chakraborty, et al.
Uncertainty in Artificial Intelligence : Proceedings of the ... Conference. Conference on Uncertainty in Artificial Intelligence
|
October 11, 2021
A Variational Approximation for Analyzing the Dynamics of Panel Data
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, et al.
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
August 18, 2021
Learning Invariant Representations using Inverse Contrastive Loss
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N Ravi, et al.
JMLR Workshop and Conference Proceedings
|
May 9, 2017
Experimental Design on a Budget for Sparse Linear Models and Applications
Sathya N Ravi, Vamsi K Ithapu, Sterling C Johnson, et al.
Page
of 42