Tag: epsilon
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Identifying All {epsilon}-Best Arms in (Misspecified) Linear Bandits
Identifying All {epsilon}-Best Arms in (Misspecified) Linear Bandits arXiv:2510.00073v1 Announce Type: new Abstract: Motivated by the need to efficiently identify multiple candidates in high trial-and-error cost tasks such as drug discovery, we propose a near-optimal algorithm to identify all {epsilon}-best arms (i.e., those at most {epsilon} worse than the optimum). Specifically, we introduce LinFACT, an…
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Optimal Subspace Embeddings: Resolving Nelson-Nguyen Conjecture Up to Sub-Polylogarithmic Factors
Optimal Subspace Embeddings: Resolving Nelson-Nguyen Conjecture Up to Sub-Polylogarithmic Factors arXiv:2508.14234v1 Announce Type: cross Abstract: We give a proof of the conjecture of Nelson and Nguyen [FOCS 2013] on the optimal dimension and sparsity of oblivious subspace embeddings, up to sub-polylogarithmic factors: For any $ngeq d$ and $epsilongeq d^{-O(1)}$, there is a random $tilde O(d/epsilon^2)times…
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Near-optimal algorithms for private estimation and sequential testing of collision probability
Near-optimal algorithms for private estimation and sequential testing of collision probability arXiv:2504.13804v1 Announce Type: new Abstract: We present new algorithms for estimating and testing emph{collision probability}, a fundamental measure of the spread of a discrete distribution that is widely used in many scientific fields. We describe an algorithm that satisfies $(alpha, beta)$-local differential privacy and…
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$(epsilon, delta)$-Differentially Private Partial Least Squares Regression
$(epsilon, delta)$-Differentially Private Partial Least Squares Regression arXiv:2412.09164v1 Announce Type: new Abstract: As data-privacy requirements are becoming increasingly stringent and statistical models based on sensitive data are being deployed and used more routinely, protecting data-privacy becomes pivotal. Partial Least Squares (PLS) regression is the premier tool for building such models in analytical chemistry, yet it…