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Compression of Individual Sequences via Variable-Rate Coding

by Jacob Ziv, Abraham Lempel - IEEE TRANSACTIONS ON INFORMATION THEORY , 1978
"... ..."
Abstract - Cited by 954 (9 self) - Add to MetaCart
Abstract not found

Universal prediction of individual sequences

by Meir Feder, Neri Merhav, Michael Gutman - IEEE Transactions on Information Theory , 1992
"... Abstruct-The problem of predicting the next outcome of an individual binary sequence using finite memory, is considered. The finite-state predictability of an infinite sequence is defined as the minimum fraction of prediction errors that can be made by any finite-state (FS) predictor. It is proved t ..."
Abstract - Cited by 181 (13 self) - Add to MetaCart
Abstruct-The problem of predicting the next outcome of an individual binary sequence using finite memory, is considered. The finite-state predictability of an infinite sequence is defined as the minimum fraction of prediction errors that can be made by any finite-state (FS) predictor. It is proved

Coding theorems for individual sequences

by Jacob Ziv - IEEE Transactions on Information Theory , 1978
"... Abstract—A quantity called the finite-state complexity is assigned to every infinite sequence of elements drawn from a finite set. This quantity characterizes the largest compression ratio that can be achieved in accurate transmission of the sequence by any finite-state encoder (and decoder). Coding ..."
Abstract - Cited by 47 (2 self) - Add to MetaCart
). Coding theorems and converses are derived for an individual sequence without any probabilistic characterization, and universal data compression algorithms are introduced that are asymptotically optimal for all sequences over a given alphabet. The finite-state complexity of a sequence plays a role similar

On Delayed Prediction of Individual Sequences

by Marcelo J. Weinberger, Erik Ordentlich , 2000
"... Prediction of individual sequences is investigated for cases in which the decision maker observes a delayed version of the sequence, or is forced to issue his/her predictions a number of steps in advance, with incomplete information. For finite action and observation spaces, it is shown that the pre ..."
Abstract - Cited by 8 (1 self) - Add to MetaCart
Prediction of individual sequences is investigated for cases in which the decision maker observes a delayed version of the sequence, or is forced to issue his/her predictions a number of steps in advance, with incomplete information. For finite action and observation spaces, it is shown

On Prediction of Individual Sequences

by Nicolò Cesa-Bianchi, Gábor Lugosi , 1998
"... Sequential randomized prediction of an arbitrary binary sequence is investigated. No assumption is made on the ..."
Abstract - Cited by 34 (5 self) - Add to MetaCart
Sequential randomized prediction of an arbitrary binary sequence is investigated. No assumption is made on the

General methods for monitoring convergence of iterative simulations

by Stephen P. Brooksand, Andrew Gelman - J. Comput. Graph. Statist , 1998
"... We generalize the method proposed by Gelman and Rubin (1992a) for monitoring the convergence of iterative simulations by comparing between and within variances of multiple chains, in order to obtain a family of tests for convergence. We review methods of inference from simulations in order to develo ..."
Abstract - Cited by 551 (8 self) - Add to MetaCart
to develop convergence-monitoring summaries that are relevant for the purposes for which the simulations are used. We recommend applying a battery of tests for mixing based on the comparison of inferences from individual sequences and from the mixture of sequences. Finally, we discuss multivariate analogues

On Prediction of Individual Sequences 1

by Nicolò Cesa-bianchi, Gábor Lugosi, N. Cesa-bianchi, G. Lugosi
"... Sequential randomized prediction of an arbitrary binary sequence is investigated. No assumption is made on the mechanism of generating the bit sequence. The goal of the predictor is to minimize its relative loss (or regret), i.e., to make almost as few mistakes as the best “expert ” in a fixed, poss ..."
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Sequential randomized prediction of an arbitrary binary sequence is investigated. No assumption is made on the mechanism of generating the bit sequence. The goal of the predictor is to minimize its relative loss (or regret), i.e., to make almost as few mistakes as the best “expert ” in a fixed

Lectures on Prediction of Individual Sequences

by Gábor Lugosi , 2001
"... ..."
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Fast and accurate short read alignment with Burrows-Wheeler transform

by Heng Li, Richard Durbin - BIOINFORMATICS, 2009, ADVANCE ACCESS , 2009
"... Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hashtable based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to a ..."
Abstract - Cited by 2096 (24 self) - Add to MetaCart
of individuals. Results: We implemented BWA, a new read alignment package that is based on backward search with Burrows-Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space

Alternative isoform regulation in human tissue transcriptomes

by Eric T. Wang, Rickard S, Shujun Luo, Irina Khrebtukova, Lu Zhang, Christine Mayr, Stephen F. Kingsmore, Gary P. Schroth, Christopher B. Burge - Nature , 2008
"... Through alternative processing of pre-mRNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes based on deep sequencing of ..."
Abstract - Cited by 545 (6 self) - Add to MetaCart
Through alternative processing of pre-mRNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes based on deep sequencing
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