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Contrastive Pre-Training for Addressing Class Imbalance in Encrypted Traffic Classification

Contrastive Pre-Training for Addressing Class Imbalance in Encrypted Traffic Classification

by instadatahelp | Sep 2, 2023 | AI Blogs

arXivLabs is a platform where collaborators can create and share new features directly on the arXiv website. Both individuals and organizations that collaborate with arXivLabs share our values of openness, community, excellence, and user data privacy. We only work...

Uncovering the Unconscious Bias Behind Benign Overfitting

by instadatahelp | Sep 2, 2023 | AI Blogs

The Implicit Bias of Benign Overfitting By Ohad Shamir; Published in 2023; Volume 24, Issue 113: Pages 1-40 Abstract Benign overfitting, a phenomenon where a predictor perfectly fits noisy training data while achieving near-optimal expected loss, has gained...
Contrastive Pre-Training for Addressing Class Imbalance in Encrypted Traffic Classification

AntM$^{2}$C: A Comprehensive Dataset for Predicting Click-Through Rate in Diverse Scenarios using Multiple Modalities

by instadatahelp | Sep 2, 2023 | AI Blogs

Click-through rate (CTR) prediction is a crucial challenge in recommendation systems. Several public CTR datasets have emerged, but they have certain limitations. Firstly, existing datasets only include data from a single scenario and same type of items, while users...

The Theoretical Equivalence of Multiple Trade-Off Curves in Evaluating Statistical Proximity

by instadatahelp | Sep 2, 2023 | AI Blogs

Theoretical Equivalence of Trade-Off Curves for Statistical Proximity Assessment Rodrigue Siry, Ryan Webster, Loic Simon, Julien Rabin; 24(185):1−34, 2023. Abstract The development of quantitative measures to assess the proximity of two probability distributions has...
Contrastive Pre-Training for Addressing Class Imbalance in Encrypted Traffic Classification

A High-dimensional Perspective on the Equivalence of Implicit and Explicit Neural Networks (arXiv:2308.16425v1 [cs.LG])

by instadatahelp | Sep 2, 2023 | AI Blogs

The effectiveness of implicit neural networks in different tasks has been proven. However, there is a need for theoretical analysis to understand the connections and distinctions between implicit and explicit networks. This study focuses on high-dimensional implicit...
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