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Conference on Empirical Methods in Natural Language Processing

作者： Yang Feng Yang Liu Qun Liu Trevor Cohn Department of Computer Science The University of Sheffield Sheffield UK State Key Laboratory on Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Sci. and Tech. Tsinghua University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781622765034

decoding algorithms for syntax based machine translation suffer from high computational complexity, a consequence of intersecting a language model with a context free grammar. Left-to-right decoding, which generates the target string in order, can improve decoding efficiency by simplifying the language model evaluation. This paper presents a novel left to right decoding algorithm for tree-to-string translation, using a bottom-up parsing strategy and dynamic future cost estimation for each partial translation. Our method outperforms previously published tree-to-string decoders, including a competing left-to-right method.

关键词： modelling languages decoding decoding algorithm machine translation syntax context-free grammars

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Generalized Higher-Order Dependency Parsing with Cube Pruning 12

Generalized Higher-Order Dependency Parsing with Cube Prunin...

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Conference on Empirical Methods in Natural Language Processing

作者： Hao Zhang Ryan McDonald Google Inc.

ISBN: (纸本)9781622765034

State-of-the-art graph-based parsers use features over higher-order dependencies that rely on decoding algorithms that are slow and difficult to generalize. On the other hand, transition-based dependency parsers can easily utilize such features without increasing the linear complexity of the shift-reduce system beyond a constant. In this paper, we attempt to address this imbalance for graph-based parsing by generalizing the Eisner (1996) algorithm to handle arbitrary features over higher-order dependencies. The generalization is at the cost of asymptotic efficiency. To account for this, cube pruning for decoding is utilized (Chiang, 2007). For the first time, label tuple and structural features such as valencies can be scored efficiently with third-order features in a graph-based parser. Our parser achieves the state-of-art unlabeled accuracy of 93.06% and labeled accuracy of 91.86% on the standard test set for English, at a faster speed than a reimplementation of the third-order model of Koo et al. (2010).

关键词： Parser Parsing decoding Cube higher-order test standards tree surgery Structural properties English Valence English language Generalization fast speed decoding algorithm

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Sublinear Time, Measurement-Optimal, Sparse Recovery For All 12

Sublinear Time, Measurement-Optimal, Sparse Recovery For All

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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete algorithms

作者： Ely Porat Martin J. Strauss Bar Ilan University University of Michigan

ISBN: (纸本)9781611972108

An approximate sparse recovery system in l_1 norm makes a small number of measurements of a noisy vector with at most k large entries and recovers those heavy hitters approximately. Formally, it consists of parameters N, k, ε, an m-by-N measurement matrix, φ, and a decoding algorithm, D. Given a vector, x, where x_k denotes the optimal k-term approximation to x, the system approximates x by {top}x = D(φx), which must satisfy ‖x{top}^ - x‖_1 ≤ (1 + ε) ‖x - x_k‖_1. Among the goals in designing such systems are minimizing the number m of measurements and the runtime of the decoding algorithm, D. We consider the "forall" model, in which a single matrix φ, possibly "constructed" non-explicitly using the probabilistic method, is used for all signals x.

关键词： decoding algorithm sublinear system recovery mechanical heart valve K CORRECTION Runtime measurement matrix deuterium ABSORBED DOSE

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Counter Braids: Asymptotic Optimality of the Message Passing decoding algorithm

Counter Braids: Asymptotic Optimality of the Message Passing...

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Annual Allerton Conference on Communication, Control, and Computing

作者： Yi Lu Andrea Montanari Balaji Prabhakar Department of Electrical Engineering Stanford University Departments of Electrical Engineering and Statistics Stanford University

ISBN: (纸本)9781424429257

A novel counter architecture, called Counter Braids, has recently been proposed for per-flow counting on high-speed links. Counter Braids has a layered structure and compresses the flow sizes as it counts. It has been shown that with a Maximum Likelihood (ML) decoding algorithm, the number of bits needed to store the size of a flow matches the entropy lower bound. As ML decoding is too complex to implement, an efficient message passing decoding algorithm has been proposed for practical purposes. The layers of Counter Braids are decoded sequentially, from the most significant to the least significant bits. In each layer, the message passing decoder solves a sparse signal recovery problem. In this paper we analyze the threshold dimensionality reduction rate (d-rate) of the message passing algorithm, and prove that it is correctly predicted by density evolution. Given a signal in R_+~n with TIE non-vanishing entries, we prove that one layer of Counter Braids can reduce its dimensionality by a factor 2.08·εlog(l/ε) + O(ε). This essentially matches the rate for sparse signal recovery via L_1 minimization, while keeping the overall complexity linear in n.

关键词： decoding algorithm message passing BRAIDING Signal restoration Counters Drill bits Pheromone a-Factor one layer

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Trait-Based Hypothesis Selection For Machine Translation 12

Trait-Based Hypothesis Selection For Machine Translation

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Conference of the North American Chapter of the Association for Computational Linguistics: human language technologies

作者： Jacob Devlin Spyros Matsoukas Raytheon BBN Technologies Cambridge MA

ISBN: (纸本)9781937284206

In the area of machine translation (MT) system combination, previous work on generating input hypotheses has focused on varying a core aspect of the MT system, such as the decoding algorithm or alignment algorithm. In this paper, we propose a new method for generating diverse hypotheses from a single MT system using traits. These traits are simple properties of the MT output such as "average output length" and "average rule length." Our method is designed to select hypotheses which vary in trait value but do not significantly degrade in BLEU score. These hypotheses can be combined using standard system combination techniques to produce a 1.2-1.5 BLEU gain on the Arabic-English NIST MT06/MT08 translation task.

关键词： machine translation Belgo-Luxembourg Economic Union MT decoding algorithm new methods

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Erasure decoding for Gabidulin Codes

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Journal of Mathematical Modelling and algorithms 2011年第3期10卷 277-291页

作者： Babindamana, Regis F. Gueye, Cheikh Thiecoumba Departement de Mathématiques Informatique Faculté des Sciences et Techniques Universite Cheikh Anta Diop Dakar Senegal

We present a new approach of the decoding algorithm for Gabidulin Codes. In the same way as efficient erasure decoding for Generalized Reed Solomon codes by using the structure of the inverse of the VanderMonde matrices, we show that, the erasure(t erasures mean that t components of a code vector are erased) decoding Gabidulin code can be seen as a computation of three matrice and an affine permutation, instead of computing an inverse from the generator or parity check matrix. This significantly reduces the decoding complexity compared to others algorithms. For t erasures with t ≤ r, where r = n - k, the erasure algorithm decoding for Gab_{n, k}(g) Gabidulin code compute the t symbols by simple multiplication of three matrices. That requires rt + r(k - 1) Galois field multiplications, t(r - 1) + (t + r)k field additions, r² + r(k + 1) field negations and t(k + 1) field inversions. © 2011 Springer Science+Business Media B.V.

关键词： Cauchy matrix decoding algorithm Gabidulin codes Generalized Reed Solomon codes Vandermonde matrix

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Unified scaling factor approach for turbo decoding algorithms

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IET COMMUNICATIONS 2010年第8期4卷 905-914页

作者： Yue, D. -W. Nguyen, H. H. Dalian Maritime Univ Coll Informat Sci & Technol Dalian Peoples R China Univ Saskatchewan Dept Elect & Comp Engn Saskatoon SK S7N 5A9 Canada

Turbo (iterative) decoding can be implemented with a large family of soft- input soft-output (SISO) algorithms, including suboptimal but practical algorithms such as the soft- output Viterbi algorithm (SOVA) and max-log-MAP algorithm. The performance with these practical algorithms can be improved with simple scaling factor methods. However, their theoretical analysis was mainly based on the relaxed assumption proposed by Papke et al. that the extrinsic information is Gaussian distributed. This study proposes a novel scaling factor approach for reducing both the overestimation of reliability values and the correlation between the intrinsic and extrinsic information. Explicit formulae for computing the scaling factors are derived based on mathematical statistics. A key difference compared to the scaling factor method of Papke et al. is that the proposed scaling factors can be computed off-line. The numerical results show that when implemented in the decoding algorithm of block component codes, the proposed scaling factor approach improves the performance of turbo decoding over additive white Gaussian noise and Rayleigh fading channels. It is superior than the method by Papke et al. in both performance and complexity.

关键词： Turbo Raleigh fading channels Scale factor decoding AWGN large family Worm gears decoding algorithm

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High-speed Transmission of Overlay Coding for Road-to-Vehicle Visible Light Communication Using LED Array and High-Speed Camera

High-speed Transmission of Overlay Coding for Road-to-Vehicl...

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Institute of Electrical and Electronics Engineers Globecom Workshops

作者： Sayaka NISHIMOTO Takaya YAMAZATO Hiraku OKADA Toshiaki FUJIT Tomohiro YENDO Shintaro ARAI Nagoya University Nagaoka University of Technology Kagawa National College of Technology

ISBN: (纸本)9781467349420

This paper aims to the improve the data rate for the visible light communication system using LED array and high-speed camera. Previously, we have proposed the decoding algorithm using inverted signals for driving situation. However, using this method the data rate become a half, because we transmit original signals and inverted signals alternately for LED array tracking. In this paper, we propose the data rate improving method for overlay coding which is coding method that overlay two data which are called as the long range data and the short range data. In the proposed method, for the long range data, we transmit original signals and inverted signals alternately. On the other hand, for the short range data, we transmit only original signals while we transmit inverted signals of long range data. We confirm that we can improve data rate as compared with the previous method.

关键词： original signal Cameras-High speed Range of a function Data transfer rates Overlay SMIM10L2A gene Light emitting diodes TRANSMITTING high speed transmission decoding algorithm signals

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The l_1 penalized decoder and its reweighted LP

The l_1 penalized decoder and its reweighted LP

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Annual Allerton Conference on Communication, Control, and Computing

作者： Xishuo Liu Stark C. Draper Benjamin Recht Department of Electrical and Computer Engineering University of Wisconsin Department of Computer Sciences University of Wisconsin

ISBN: (纸本)9781467345378

Linear programming (LP) decoding for low density parity check (LDPC) codes proposed by Feldman et al. has attracted considerable attention in recent years. Despite having theoretical guarantees in some regimes, at low SNRs LP decoding is observed to have worse error performance than belief propagation (BP) decoding. In this paper, we present a novel decoding algorithm obtained by trying to solve a non-convex optimization problem using the alternating direction method of multipliers (ADMM). This non-convex problem is constructed by adding an l_1 penalty term to the LP decoding objective. The goal of the penalty term is to make "pseudocodewords", which are the non-integer vertices of the LP relaxation to which the LP decoder fails, more costly. We name this the "l_1 penalized decoder". We also develop a reweighted LP decoding algorithm base on this l_1 penalized objective. We show that this reweighted LP has an improved theoretical recovery threshold compared to the original LP. In addition, simulations show that, in comparison to LP decoding, these two decoders both achieve significantly lower error rates and are not observed to have an "error floor". In particular, the l_1 penalized decoder meets or outperforms the BP decoder at all SNRs.

关键词： decoders decoding Error analysis error performance decoding algorithm Non-Convex penalty

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Hierarchical Constrained Coding for Floating-Gate to Floating-Gate Coupling Mitigation in Flash Memory

Hierarchical Constrained Coding for Floating-Gate to Floatin...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Motwani, Ravi Intel Corp NVM Solut Grp Santa Clara CA 95051 USA

ISBN: (纸本)9781424492688

Flash memory comprises of grid of cells arranged in a rectangular lattice. A cell is a floating gate and the information is stored as charge in these floating gates. A multi-level-cell (MLC) stores more than one bit per cell. Programming of a cell in NAND Flash is attained by Fowler-Nordhiem tunneling till the ideal programmed voltage is attained. However, due to programming time constraints, some tolerance is accepted and the actual programmed voltage is allowed to be within some range of the ideal value. The read level is a random variable with some distribution around the mean programming level. Errors occur during reads because of overlaps of the level distributions. If the raw bit error rate has to be kept low, the distributions must be narrow. One of the impairment which broadens the distributions is the capacitive coupling between neighboring cells. This phenomenon called as inter-cell-interference due to floating-gate to floating-gate coupling can be from mild to extreme. To combat this effect, constrained coding is a possible solution. Constrained coding entails forbidding certain adjacent-cell charge-level combinations. There can be various types of constrained codes, one type of constrained codes assumes that level information is available while decoding all pages [1]. However, due to read latency requirements, level information may not be available while reading all pages. In this paper, constrained codes are proposed which do not need level information while decoding all pages and hence the average read latency is reduced. Error propagation is a crucial degrading factor for constrained decoding and the codes proposed are robust to channel noise. A new decoding algorithm which keeps synchronization which is crucial to contain error propagation is also proposed.

关键词： decoding Encoding Flash memory Indexes Maximum likelihood estimation Noise measurement Synchronization capacitive coupling decoding algorithm error propagation flash memories flash memory floating-gate coupling mitigation hierarchical constrained coding hot-electron injection intercell-interference multilevel-cell neighboring cells programming time constraints rectangular lattice

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