Primal beats dual on online packing LPs in the random-order model
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Publication:5259564
DOI10.1145/2591796.2591810zbMath1315.68291arXiv1311.2578OpenAlexW2086189137MaRDI QIDQ5259564
Andreas Tönnis, Thomas Kesselheim, Berthold Vöcking, Klaus Radke
Publication date: 26 June 2015
Published in: Proceedings of the forty-sixth annual ACM symposium on Theory of computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1311.2578
Linear programming (90C05) Randomized algorithms (68W20) Online algorithms; streaming algorithms (68W27)
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Uses Software
Cites Work
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- Efficient algorithms for privately releasing marginals via convex relaxations
- The Geometry of Differential Privacy: The Small Database and Approximate Cases
- Faster Algorithms for Privately Releasing Marginals
- Private Learning and Sanitization: Pure vs. Approximate Differential Privacy
- Privately Releasing Conjunctions and the Statistical Query Barrier
- On the geometry of differential privacy
- Interactive privacy via the median mechanism
- The price of privately releasing contingency tables and the spectra of random matrices with correlated rows
- Lower Bounds in Differential Privacy
- Iterative Constructions and Private Data Release
- Characterizing the sample complexity of private learners
- Faster private release of marginals on small databases
- Bounds on the Sample Complexity for Private Learning and Private Data Release
- Differential Privacy and the Fat-Shattering Dimension of Linear Queries
- Our Data, Ourselves: Privacy Via Distributed Noise Generation
- New Efficient Attacks on Statistical Disclosure Control Mechanisms
- Collusion-secure fingerprinting for digital data
- On the complexity of differentially private data release
- Advances in Cryptology – CRYPTO 2004
- Answering n {2+o(1)} counting queries with differential privacy is hard
- Theory of Cryptography
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