by instadatahelp | Sep 2, 2023 | AI Blogs
FLIP: A Privacy-Preserving Mechanism for Time Series Data Authors: Tucker McElroy, Anindya Roy, Gaurab Hore; Published in Journal of Machine Learning Research, Volume 24, Issue 111, Pages 1-29, 2023. Abstract Ensuring privacy in released data is a crucial objective...
by instadatahelp | Sep 2, 2023 | AI Blogs
[Submitted on 31 Aug 2023] Click here to download a PDF of the research paper titled “Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff” by Satoshi Suzuki and 6 other authors. Download PDF Abstract: This...
by instadatahelp | Sep 2, 2023 | AI Blogs
Metrizing Weak Convergence with Maximum Mean Discrepancies Authors: Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey; Volume 24, Issue 184, Pages 1-20, 2023. Abstract This paper investigates the maximum mean discrepancies (MMD) that can be...
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...
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...
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...
