Sathya N. Ravi

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 45

Top Topics

Invariant Representations

Blind Deconvolution

Top Venues

Publications

Homaira Huda Shomee, Zhu Wang, Sathya N. Ravi, Sourav Medya
A Comprehensive Survey on AI-based Methods for Patents. CoRR (2024)
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan, Sathya N. Ravi
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization. ICLR (2024)
Zhu Wang, Sourav Medya, Sathya N. Ravi
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis. CoRR (2023)
Harsh Mishra, Jurijs Nazarovs, Manmohan Dogra, Sathya N. Ravi
Using Intermediate Forward Iterates for Intermediate Generator Optimization. CoRR (2023)
Ronak Mehta, Sathya N. Ravi, Vikas Singh
Robustness and Convergence of Mirror Descent for Blind Deconvolution. ICASSP (2023)
Zhu Wang, Praveen Raj Veluswami, Harsh Mishra, Sathya N. Ravi
Accelerated Neural Network Training with Rooted Logistic Objectives. CoRR (2023)
Zhu Wang, Sourav Medya, Sathya N. Ravi
Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis. NeurIPS (2023)
Sourav Pal, Zhanpeng Zeng, Sathya N. Ravi, Vikas Singh
Controlled Differential Equations on Long Sequences via Non-standard Wavelets. ICML (2023)
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan, Sathya N. Ravi
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization. CoRR (2023)
Tuan Q. Dinh, Yunyang Xiong, Zhichun Huang, Tien Vo, Akshay Mishra, Won Hwa Kim, Sathya N. Ravi, Vikas Singh
Performing Group Difference Testing on Graph Structured Data From GANs: Analysis and Applications in Neuroimaging. IEEE Trans. Pattern Anal. Mach. Intell. 44 (2) (2022)
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, Sathya N. Ravi, Vikas Singh
Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data. CoRR (2022)
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CoRR (2022)
Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi
Deep Unlearning via Randomized Conditionally Independent Hessians. CVPR (2022)
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CVPR (2022)
Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi
Deep Unlearning via Randomized Conditionally Independent Hessians. CoRR (2022)
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh
Learning Invariant Representations using Inverse Contrastive Loss. AAAI (2021)
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, Sathya N. Ravi, Vikas Singh
A variational approximation for analyzing the dynamics of panel data. UAI (2021)
Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Moo Fung, Vikas Singh
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling. ICML (2021)
Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling. CoRR (2021)
Zihang Meng, Vikas Singh, Sathya N. Ravi
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators. CoRR (2021)
Zihang Meng, Sathya N. Ravi, Vikas Singh
Physarum Powered Differentiable Linear Programming Layers and Applications. AAAI (2021)
Zihang Meng, Lopamudra Mukherjee, Yichao Wu, Vikas Singh, Sathya N. Ravi
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs. NeurIPS (2021)
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh
Learning Invariant Representations using Inverse Contrastive Loss. CoRR (2021)
Zihang Meng, Vikas Singh, Sathya N. Ravi
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators. ICCV (2021)
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. CoRR (2020)
Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains. AAAI (2020)
Zihang Meng, Sathya N. Ravi, Vikas Singh
Physarum Powered Differentiable Linear Programming Layers and Applications. CoRR (2020)
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. ECCV (12) (2020)
Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh, Sathya N. Ravi, Vikas Singh
Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations. CVPR (2020)
Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization offers Significant Performance and Efficiency Gains. CoRR (2019)
Sathya N. Ravi, Maxwell D. Collins, Vikas Singh
A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees. INFORMS J. Optim. 1 (2) (2019)
Vishnu Suresh Lokhande, Sathya N. Ravi, Songwong Tasneeyapant, Abhay Venkatesh, Vikas Singh
Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently. CoRR (2019)
Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence. AAAI (2019)
Sathya N. Ravi
Numerical Optimization to AI, and Back. AAAI (2019)
Yiyou Sun, Sathya N. Ravi, Vikas Singh
Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks. ICCV (2019)
Sathya N. Ravi, Ronak Mehta, Vikas Singh
Robust Blind Deconvolution via Mirror Descent. CoRR (2018)
Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning. CVPR (2018)
Lopamudra Mukherjee, Sathya N. Ravi, Jiming Peng, Vikas Singh
A Biresolution Spectral Framework for Product Quantization. CVPR (2018)
Sathya N. Ravi, Tuan Dinh, Vishnu Sai Rao Lokhande, Vikas Singh
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision. CoRR (2018)
Sathya N. Ravi, Maxwell D. Collins, Vikas Singh
A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees. CoRR (2017)
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation. CoRR (2017)
Sathya N. Ravi, Yunyang Xiong, Lopamudra Mukherjee, Vikas Singh
Filter Flow Made Practical: Massively Parallel and Lock-Free. CVPR (2017)
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
On the interplay of network structure and gradient convergence in deep learning. Allerton (2016)
Sathya N. Ravi, Vamsi K. Ithapu, Sterling C. Johnson, Vikas Singh
Experimental Design on a Budget for Sparse Linear Models and Applications. ICML (2016)
Seong Jae Hwang, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh
Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks. CVPR (2016)
Lopamudra Mukherjee, Sathya N. Ravi, Vamsi K. Ithapu, Tyler Holmes, Vikas Singh
An NMF Perspective on Binary Hashing. ICCV (2015)
Won Hwa Kim, Sathya N. Ravi, Sterling C. Johnson, Ozioma C. Okonkwo, Vikas Singh
On Statistical Analysis of Neuroimages with Imperfect Registration. ICCV (2015)
Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh
A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer. ICCV (2015)
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
On the interplay of network structure and gradient convergence in deep learning. CoRR (2015)
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
Convergence of gradient based pre-training in Denoising autoencoders. CoRR (2015)