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Results 11 - 20
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628,717
Learning to Parse Natural Language with Maximum Entropy Models
, 1999
"... This paper presents a machine learning system for parsing natural language that learns from manually parsed example sentences, and parses unseen data at state-of-the-art accuracies. Its machine learning technology, based on the maximum entropy framework, is highly reusable and not specific to the pa ..."
Abstract
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Cited by 191 (0 self)
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This paper presents a machine learning system for parsing natural language that learns from manually parsed example sentences, and parses unseen data at state-of-the-art accuracies. Its machine learning technology, based on the maximum entropy framework, is highly reusable and not specific
Image Classification using Super-Vector Coding of Local Image Descriptors
"... Abstract. This paper introduces a new framework for image classification using local visual descriptors. The pipeline first performs a nonlinear feature transformation on descriptors, then aggregates the results together to form image-level representations, and finally applies a classification model ..."
Abstract
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Cited by 102 (2 self)
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model. For all the three steps we suggest novel solutions which make our approach appealing in theory, more scalable in computation, and transparent in classification. Our experiments demonstrate that the proposed classification method achieves state-of-the-art accuracy on the well-known PASCAL
Linear-Time Dependency Analysis for Japanese
"... We present a novel algorithm for Japanese dependency analysis. The algorithm allows us to analyze dependency structures of a sentence in linear-time while keeping a state-of-the-art accuracy. In this paper, we show a formal description of the algorithm and discuss it theoretically with respect to ti ..."
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Cited by 3 (1 self)
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We present a novel algorithm for Japanese dependency analysis. The algorithm allows us to analyze dependency structures of a sentence in linear-time while keeping a state-of-the-art accuracy. In this paper, we show a formal description of the algorithm and discuss it theoretically with respect
Turning on the Turbo: Fast Third-Order Non-Projective Turbo Parsers
, 2013
"... We present fast, accurate, direct non-projective dependency parsers with third-order features. Our approach uses AD3, an accelerated dual decomposition algorithm which we extend to handle specialized head automata and sequential head bigram models. Experiments in fourteen languages yield parsing spe ..."
Abstract
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Cited by 18 (6 self)
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speeds competitive to projective parsers, with state-of-the-art accuracies for the largest datasets (English, Czech, and German)
Computer Vision for Head Pose Estimation: Review of a Competition
"... Abstract. This paper studies the prediction of head pose from still images, and summarizes the outcome of a recently organized competition, where the task was to predict the yaw and pitch angles of an image dataset with 2790 samples with known angles. The competition received 292 entries from 52 par ..."
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participants, the best ones clearly exceeding the state-of-the-art accuracy. In this paper, we present the key methodologies behind selected top methods, summarize their prediction accuracy and compare with the current state of the art.
Hierarchical phrase-based translation
- Computational Linguistics
, 2007
"... We present a statistical machine translation model that uses hierarchical phrases—phrases that contain subphrases. The model is formally a synchronous context-free grammar but is learned from a parallel text without any syntactic annotations. Thus it can be seen as combining fundamental ideas from b ..."
Abstract
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Cited by 588 (9 self)
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the Alignment Template System, a state-of-the-art phrasebased system. 1.
Discriminant Pattern Recognition Using Transformation Invariant Neurons
- Neural Computation
, 2000
"... To overcome the problem of invariant pattern recognition Simard et al. proposed a successful nearest-neighbor approach based on tangent distance, attaining state-of-the-art accuracy. Since this approach needs great computational and memory e#ort, Hastie et al. proposed an algorithm (HSS) based o ..."
Abstract
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Cited by 8 (4 self)
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To overcome the problem of invariant pattern recognition Simard et al. proposed a successful nearest-neighbor approach based on tangent distance, attaining state-of-the-art accuracy. Since this approach needs great computational and memory e#ort, Hastie et al. proposed an algorithm (HSS) based
A Simple and scalable response prediction for display advertising
"... Clickthrough and conversation rates estimation are two core predictions tasks in display advertising. We present in this paper a machine learning framework based on logistic regression that is specifically designed to tackle the specifics of display advertising. The resulting system has the followin ..."
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Cited by 8 (4 self)
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the following characteristics: it is easy to implement and deploy; it is highly scalable (we have trained it on terabytes of data); and it provides models with state-of-the-art accuracy.
A comparison and evaluation of multi-view stereo reconstruction algorithms
- In IEEE CVPR
, 2006
"... This paper presents a quantitative comparison of several multi-view stereo reconstruction algorithms. Until now, the lack of suitable calibrated multi-view image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we rst survey multi-view stereo a ..."
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Cited by 533 (15 self)
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quantitative comparison of state-of-the-art multi-view stereo reconstruction algorithms on six bench-mark datasets. The datasets, evaluation details, and in-structions for submitting new models are available online at
Results 11 - 20
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628,717
