Sathya N. Ravi

CoRR, 2023

Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis.

[BibT_eX]

[DOI]

Zhu Wang

Sourav Medya

CoRR, 2023

Using Intermediate Forward Iterates for Intermediate Generator Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis.

[BibT_eX]

[DOI]

Zhu Wang

Sourav Medya

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Controlled Differential Equations on Long Sequences via Non-standard Wavelets.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Robustness and Convergence of Mirror Descent for Blind Deconvolution.

[BibT_eX]

[DOI]

Ronak Mehta

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Performing Group Difference Testing on Graph Structured Data From GANs: Analysis and Applications in Neuroimaging.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data.

[BibT_eX]

[DOI]

Jurijs Nazarovs

Rudrasis Chakraborty

CoRR, 2022

Deep Unlearning via Randomized Conditionally Independent Hessians.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets.

[BibT_eX]

[DOI]

Rudrasis Chakraborty

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

A variational approximation for analyzing the dynamics of panel data.

[BibT_eX]

[DOI]

Jurijs Nazarovs

Rudrasis Chakraborty

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators.

[BibT_eX]

[DOI]

Zihang Meng

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Physarum Powered Differentiable Linear Programming Layers and Applications.

[BibT_eX]

[DOI]

Zihang Meng

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Learning Invariant Representations using Inverse Contrastive Loss.

[BibT_eX]

[DOI]

Aditya Kumar Akash

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret.

[BibT_eX]

[DOI]

Aditya Kumar Akash

Proceedings of the Computer Vision - ECCV 2020, 2020

Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations.

[BibT_eX]

[DOI]

Abhay Venkatesh

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees.

[BibT_eX]

[DOI]

Maxwell D. Collins

INFORMS J. Optim., April, 2019

Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently.

[BibT_eX]

[DOI]

Abhay Venkatesh

CoRR, 2019

Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks.

[BibT_eX]

[DOI]

Yiyou Sun

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence.

[BibT_eX]

[DOI]

Tuan Dinh

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Numerical Optimization to AI, and Back.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Robust Blind Deconvolution via Mirror Descent.

[BibT_eX]

[DOI]

Ronak Mehta

CoRR, 2018

Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision.

[BibT_eX]

[DOI]

Tuan Dinh

Vishnu Sai Rao Lokhande

CoRR, 2018

A Biresolution Spectral Framework for Product Quantization.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Tensorize, Factorize and Regularize: Robust Visual Relationship Learning.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation.

[BibT_eX]

[DOI]

CoRR, 2017

Filter Flow Made Practical: Massively Parallel and Lock-Free.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease.

[BibT_eX]

[DOI]

Hao Henry Zhou

Sathya Narayanan Ravi

Grace Wahba

Sterling C. Johnson

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Experimental Design on a Budget for Sparse Linear Models and Applications.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

On the interplay of network structure and gradient convergence in deep learning.

[BibT_eX]

[DOI]

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015

Convergence of gradient based pre-training in Denoising autoencoders.

[BibT_eX]

[DOI]