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Composable memory transactions
 In Symposium on Principles and Practice of Parallel Programming (PPoPP
, 2005
"... Atomic blocks allow programmers to delimit sections of code as ‘atomic’, leaving the language’s implementation to enforce atomicity. Existing work has shown how to implement atomic blocks over wordbased transactional memory that provides scalable multiprocessor performance without requiring changes ..."
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Cited by 509 (43 self)
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repeatedly in an atomic block), (3) we use runtime filtering to detect duplicate log entries that are missed statically, and (4) we present a series of GCtime techniques to compact the logs generated by longrunning atomic blocks. Our implementation supports shortrunning scalable concurrent benchmarks
Exact Matrix Completion via Convex Optimization
, 2008
"... We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can perfe ..."
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Cited by 873 (26 self)
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perfectly recover most lowrank matrices from what appears to be an incomplete set of entries. We prove that if the number m of sampled entries obeys m ≥ C n 1.2 r log n for some positive numerical constant C, then with very high probability, most n × n matrices of rank r can be perfectly recovered
The Power of Convex Relaxation: NearOptimal Matrix Completion
, 2009
"... This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a great number of applications, including the famous Netflix Prize and other similar questions in collaborative filtering. In ..."
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Cited by 359 (7 self)
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is on the order of the information theoretic limit (up to logarithmic factors). This convex program simply finds, among all matrices consistent with the observed entries, that with minimum nuclear norm. As an example, we show that on the order of nr log(n) samples are needed to recover a random n × n matrix
Secure Audit Logs to Support Computer Forensics
, 1998
"... In many realworld applications, sensitive information must be kept in log les on an untrusted machine. In the event that an attacker captures this machine, we would like to guarantee that he will gain little or no information from the log les and to limit his ability to corrupt the log les. We desc ..."
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Cited by 160 (0 self)
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describe a computationally cheap method for making all log entries generated prior to the logging machine's compromise impossible for the attacker to read, and also impossible to undetectably modify or destroy.
Analysis of a very large AltaVista query log
, 1998
"... In this paper we present an analysis of a 280 GB AltaVista Search Engine query log consisting of approximately 1 billion entries for search requests over a period of six weeks. This represents approximately 285 million user sessions, each an attempt to fill a single information need. We present an a ..."
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Cited by 195 (2 self)
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In this paper we present an analysis of a 280 GB AltaVista Search Engine query log consisting of approximately 1 billion entries for search requests over a period of six weeks. This represents approximately 285 million user sessions, each an attempt to fill a single information need. We present
Cryptographic Support for Secure Logs on Untrusted Machines
 IN PROCEEDINGS OF 7TH USENIX SECURITY SYMPOSIUM
, 1998
"... In many realworld applications, sensitive information must be kept in log files on an untrusted machine. In the event that an attacker captures this machine, we would like to guarantee that he will gain little or no information from the log files and to limit his ability to corrupt the log files. W ..."
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Cited by 97 (2 self)
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. We describe a computationally cheap method for making all log entries generated prior to the logging machine's compromise impossible for the attacker to read, and also impossible to undetectably modify or destroy.
Matrix Completion with Noise
"... On the heels of compressed sensing, a remarkable new field has very recently emerged. This field addresses a broad range of problems of significant practical interest, namely, the recovery of a data matrix from what appears to be incomplete, and perhaps even corrupted, information. In its simplest ..."
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Cited by 255 (13 self)
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that matrix completion is provably accurate even when the few observed entries are corrupted with a small amount of noise. A typical result is that one can recover an unknown n × n matrix of low rank r from just about nr log 2 n noisy samples with an error which is proportional to the noise level. We present
Backtracking intrusions
, 2003
"... Analyzing intrusions today is an arduous, largely manual task because system administrators lack the information and tools needed to understand easily the sequence of steps that occurred in an attack. The goal of BackTracker is to identify automatically potential sequences of steps that occurred in ..."
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Cited by 240 (11 self)
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as honeypots. In each case, BackTracker is able to highlight effectively the entry point used to gain access to the system and the sequence of steps from that entry point to the point at which we noticed the intrusion. The logging required to support BackTracker added 9 % overhead in running time and generated
Sparsity and Incoherence in Compressive Sampling
, 2006
"... We consider the problem of reconstructing a sparse signal x 0 ∈ R n from a limited number of linear measurements. Given m randomly selected samples of Ux 0, where U is an orthonormal matrix, we show that ℓ1 minimization recovers x 0 exactly when the number of measurements exceeds m ≥ Const · µ 2 (U) ..."
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Cited by 238 (13 self)
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) · S · log n, where S is the number of nonzero components in x 0, and µ is the largest entry in U properly normalized: µ(U) = √ n · maxk,j Uk,j. The smaller µ, the fewer samples needed. The result holds for “most ” sparse signals x 0 supported on a fixed (but arbitrary) set T. Given T, if the sign of x 0
A visual approach for monitoring logs
 In The Proceedings of the 12th Systems Administration Conference (LISA ’98
, 1998
"... Analyzing and monitoring logs that portray system, user, and network activity is essential to meet the requirements of high security and optimal resource availability. While most systems now possess satisfactory logging facilities, the tools to monitor and interpret such event logs are still in thei ..."
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Cited by 51 (1 self)
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in their infancy. This paper describes an approach to relieve system and network administrators from manually scanning sequences of log entries. An experimental system based on unsupervised neural networks and spring layouts to automatically classify events contained in logs is explained, and the use
Results 1  10
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