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Found 5 papers, 1 papers with code
Concurrent Shuffle Differential Privacy Under Continual Observation
the counter problem) and show that the concurrent shuffle model allows for significantly improved error compared to a standard (single) shuffle model.
Prompt-to-Prompt Image Editing with Cross Attention Control
Editing is challenging for these generative models, since an innate property of an editing technique is to preserve most of the original image, while in the text-based models, even a small modification of the text prompt often leads to a completely different outcome.
Ranked #14 on
Text-based Image Editing
on PIE-Bench
Differentially Private Multi-Armed Bandits in the Shuffle Model
We give an $(\varepsilon,\delta)$-differentially private algorithm for the multi-armed bandit (MAB) problem in the shuffle model with a distribution-dependent regret of $O\left(\left(\sum_{a\in [k]:\Delta_a>0}\frac{\log T}{\Delta_a}\right)+\frac{k\sqrt{\log\frac{1}{\delta}}\log T}{\varepsilon}\right)$, and a distribution-independent regret of $O\left(\sqrt{kT\log T}+\frac{k\sqrt{\log\frac{1}{\delta}}\log T}{\varepsilon}\right)$, where $T$ is the number of rounds, $\Delta_a$ is the suboptimality gap of the arm $a$, and $k$ is the total number of arms.
Locality Sensitive Hashing for Efficient Similar Polygon Retrieval
Find the vertical translation of a function $ f $ that is closest in $ L_1 $ distance to a function $ g $.
Locality Sensitive Hashing for Set-Queries, Motivated by Group Recommendations
For example, we can take $ s(p, x) $ to be the angular similarity between $ p $ and $ x $ (i. e., $1-{\angle (x, p)}/{\pi}$), and aggregate by arithmetic or geometric averaging, or taking the lowest similarity.
