Salimeh Yasaei Sekeh | DeepAI

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∙ 05/11/2023

Promise and Limitations of Supervised Optimal Transport-Based Graph Summarization via Information Theoretic Measures

Graph summarization is the problem of producing smaller graph representa...

5 Sepideh Neshatfar, et al. ∙

∙ 10/28/2022

Improving Hyperspectral Adversarial Robustness using Ensemble Networks in the Presences of Multiple Attacks

Semantic segmentation of hyperspectral images (HSI) has seen great strid...

0 Nicholas Soucy, et al. ∙

∙ 04/26/2022

Theoretical Understanding of the Information Flow on Continual Learning Performance

Continual learning (CL) is a setting in which an agent has to learn from...

12 Josh Andle, et al. ∙

∙ 04/14/2022

Q-TART: Quickly Training for Adversarial Robustness and in-Transferability

Raw deep neural network (DNN) performance is not enough; in real-world s...

8 Madan Ravi Ganesh, et al. ∙

∙ 03/22/2022

The Stanford Drone Dataset is More Complex than We Think: An Analysis of Key Characteristics

Several datasets exist which contain annotated information of individual...

7 Joshua Andle, et al. ∙

∙ 03/09/2022

CEU-Net: Ensemble Semantic Segmentation of Hyperspectral Images Using Clustering

Most semantic segmentation approaches of Hyperspectral images (HSIs) use...

9 Nicholas Soucy, et al. ∙

∙ 06/22/2020

Slimming Neural Networks using Adaptive Connectivity Scores

There are two broad approaches to deep neural network (DNN) pruning: 1) ...

30 Madan Ravi Ganesh, et al. ∙

∙ 03/18/2020

MINT: Deep Network Compression via Mutual Information-based Neuron Trimming

Most approaches to deep neural network compression via pruning either ev...

24 Madan Ravi Ganesh, et al. ∙

∙ 10/02/2019

Geometric Online Adaptation: Graph-Based OSFS for Streaming Samples

Feature selection seeks a curated subset of available features such that...

6 Salimeh Yasaei Sekeh, et al. ∙

∙ 05/21/2019

Geometric Estimation of Multivariate Dependency

This paper proposes a geometric estimator of dependency between a pair o...

0 Salimeh Yasaei Sekeh, et al. ∙

∙ 02/10/2019

Feature Selection for multi-labeled variables via Dependency Maximization

Feature selection and reducing the dimensionality of data is an essentia...

0 Salimeh Yasaei Sekeh, et al. ∙

∙ 11/15/2018

Learning to Bound the Multi-class Bayes Error

In the context of supervised learning, meta learning uses features, meta...

0 Salimeh Yasaei Sekeh, et al. ∙

∙ 10/01/2018

Convergence Rates for Empirical Estimation of Binary Classification Bounds

Bounding the best achievable error probability for binary classification...

0 Salimeh Yasaei Sekeh, et al. ∙

∙ 02/13/2018

A Dimension-Independent discriminant between distributions

Henze-Penrose divergence is a non-parametric divergence measure that can...

0 Salimeh Yasaei Sekeh, et al. ∙

∙ 02/17/2017

Direct Estimation of Information Divergence Using Nearest Neighbor Ratios

We propose a direct estimation method for Rényi and f-divergence measure...

0 Morteza Noshad, et al. ∙

∙ 09/13/2016

Information Theoretic Structure Learning with Confidence

Information theoretic measures (e.g. the Kullback Liebler divergence and...

0 Kevin R. Moon, et al. ∙