A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Fast learning of document ranking functions with the committee perceptron
2008
Proceedings of the international conference on Web search and web data mining - WSDM '08
Preserved Fulltext
We apply this agorithm to the problem of learning ranking functions for document retrieval, known as the "Learning to Rank" problem. ...
This paper presents a new variant of the perceptron algorithm using selective committee averaging (or voting). ...
CONCLUSION & FUTURE WORK In this paper we present a new variant of the perceptron algorithm, the committee perceptron, and applied it to the problem of learning document ranking functions. ...
doi:10.1145/1341531.1341542
dblp:conf/wsdm/ElsasCC08
fatcat:jz6fzvtbqfezffbcja3e6luhdu
Robust Online Learning to Rank via Selective Pairwise Approach Based on Evaluation Measures
2013
Transactions of the Japanese society for artificial intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
The basic strategy of our method is to select the most effective document pair to minimize the objective function using an entered query present in the training data, and then updates the current weight ...
vector by using only the selected document pair instead of using all document pairs in the query. ...
Perceptron and the batch learning to rank algorithm Rank-ingSVM. ...
doi:10.1527/tjsai.28.22
fatcat:umoorrpd4fgcjcj4oagh3xos3e
Online learning from click data for sponsored search
2008
Proceeding of the 17th international conference on World Wide Web - WWW '08
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Furthermore, we find that online multilayer perceptron learning, based on a small set of features representing content similarity of different kinds, significantly outperforms an information retrieval ...
We investigate the sponsored search problem from a machine learning perspective with respect to three main sub-problems: how to use click data for training and evaluation, which learning framework is more ...
To improve the expressive power of our ranking functions, within the online perceptron approach, we experimented also with multilayer models. ...
doi:10.1145/1367497.1367529
dblp:conf/www/CiaramitaMP08
fatcat:qmgw72nkgbgrvld3afm7ybsl3a
Recall Systems: Effcient Learning and Use of Category Indices
2007
Journal of machine learning research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
We introduce the framework of recall systems for efficient learning and retrieval of categories when the number of categories is large. ...
In our experiments, the index is learned within minutes, and reduces the number of categories by several orders of magnitude, without affecting the quality of classification overall. ...
Acknowledgements We thank Thomas Pierce, Dennis DeCoste, and Kevin Lang for pointers, discussions, or assistance, and the anonymous reviewers for their comments and suggestions. ...
dblp:journals/jmlr/MadaniGKS07
fatcat:lsnf2ple2rfohdfuptrmrtxwva
A Survey of Handwritten Character Recognition with MNIST and EMNIST
2019
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To the best of our knowledge, this paper is the first exhaustive and updated review of this dataset; there are some online rankings, but they are outdated, and most published papers survey only closely ...
deep learning techniques over this dataset. ...
[78] , where they proposed the use of deep convolutional extreme learning machine, where gradient descent is not used to train the network, allowing a very fast learning stage (only 21 min using CPU, ...
doi:10.3390/app9153169
fatcat:ifyi7crq3fdgtmowyojetsukte
Large-Scale Many-Class Learning
[chapter]
2008
Proceedings of the 2008 SIAM International Conference on Data Mining
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2012; you can also visit the original URL.
The file type is application/pdf.
On problems with hundreds of thousands of instances and thousands of categories, the index is learned in minutes, while other methods can take orders of magnitude longer. ...
The candidates can then be ranked and the ranking or the scores can be used for category assignment. We present novel online index learning algorithms. ...
Acknowledgements Many thanks to Dennis DeCoste, Scott Gaffney, Sathiya Keerthy, John Langford, Chih-Jen Lin, Kishore Papineni, Lance Riedel, and the machine learning group at Yahoo! ...
doi:10.1137/1.9781611972788.76
dblp:conf/sdm/MadaniC08
fatcat:tfgy3lwornftxoq3b2av4gvj44
Evaluation of Profession Predictions for Today and the Future with Machine Learning Methods : Emperical Evidence From Turkey
2021
Journal of Polytechnic
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Multi Layer Perceptron (MLP) Perceptron is the mathematical function that models a neuron in the simplest way. Perceptron consists of one or more input values, processor and one output value. ...
The input function of perceptron algorithm is shown in Figure 5 . In a generalized perceptron algorithm, the total value is found by adding the products of n input values and weights. ...
CONFLICT OF INTEREST There is no conflict of interest in this study. ...
doi:10.2339/politeknik.985534
fatcat:67pqkybk25g2tns34bmkbfkrnm
SOLAR: Scalable Online Learning Algorithms for Ranking
2015
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To overcome the limitations, this paper presents SO-LAR -a new framework of Scalable Online Learning Algorithms for Ranking, to tackle the challenge of scalable learning to rank. ...
We conduct extensive empirical studies by comparing our SOLAR algorithms with conventional learning to rank algorithms on benchmark testbeds, in which promising results validate the efficacy and scalability ...
Acknowledgments This work was supported by Singapore MOE tier 1 research grant (C220/MSS14C003) and the National Nature Science Foundation of China (61428207). ...
doi:10.3115/v1/p15-1163
dblp:conf/acl/WangWZH15
fatcat:vx62h4zrijcbvb6bucqn2m73fq
A learning rule for very simple universal approximators consisting of a single layer of perceptrons
2008
Neural Networks
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
approximators for arbitrary continuous functions with values in [0, 1] if one views the fraction of perceptrons that output 1 as the analog output of the parallel perceptron. ...
In spite of their simplicity, such circuits can compute any Boolean function if one views the majority of the binary perceptron outputs as the binary output of the parallel perceptron, and they are universal ...
Note that the output value of this gate grows with the rank of x n in the linear order of the numbers {x 1 , . . . , x n }. Theorem 2.1. ...
doi:10.1016/j.neunet.2007.12.036
pmid:18249524
fatcat:75kvkyccgnfqhpyib6u3dk754e
Rank learning for factoid question answering with linguistic and semantic constraints
2010
Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. ...
The framework supports the checking of constraints of arbitrary length relating any number of keywords. ...
The Committee Perceptron algorithm is a generalization of previous Perceptron variants [5] , and is adapted for learning ranking functions based on preferences between pairs of judged passages. ...
doi:10.1145/1871437.1871498
dblp:conf/cikm/BilottiECN10
fatcat:3kvhb33w3fh3lbijolegmsm7qq
Linguistic and semantic passage retrieval strategies for question answering
2011
SIGIR Forum
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Bag-of-words IR retrieves documents matching a query, but the QA system really needs documents that contain answers. ...
This thesis proposes two linguistic and semantic passage retrieval methods for QA, one based on structured retrieval and the other on rank-learning techniques. ...
See
Committee Perceptron The Committee Perceptron is an on-line algorithm for learning linear ranking functions for learning-to-rank tasks [16] . ...
doi:10.1145/1924475.1924495
fatcat:cbzirz6ua5bpnndsn4zs7zx5uy
Information Retrieval Features for Personality Traits
2015
Conference and Labs of the Evaluation Forum
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The main goal was to test the use of features derived from Information Retrieval to identify the personality traits of the author of a given text. ...
This paper describes the features, the classification algorithms employed, and how the experiments were run. Also, I provide a comparative analysis of my results compared to those of other groups. ...
I thank to Viviane Pereira Moreira for their help in the final revision of this paper. ...
dblp:conf/clef/Weren15
fatcat:nxnxnl2jmvbzjfgcd24b2len3m
A cross-benchmark comparison of 87 learning to rank methods
2015
Information Processing & Management
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Learning to rank is an increasingly important scientific field that comprises the use of machine learning for the ranking task. ...
Our comparison methodology consists of two components: 1) Normalized Winning Number, which gives insight in the ranking accuracy of the learning to rank method, and 2) Ideal Winning Number, which gives ...
Fast learning of
document ranking functions with the committee perceptron. In Proceed-
ings of the 2008 International Conference on Web Search and Data Mining
(WSDM), pages 55-64. ...
doi:10.1016/j.ipm.2015.07.002
fatcat:vityxuoyxzfezhdizq7sfofwka
On updates that constrain the features' connections during learning
2008
Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2012; you can also visit the original URL.
The file type is application/pdf.
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. ...
We empirically explore the methods, and compare performance to previous indexing techniques, developed with the same goals, as well as other online algorithms based on prototype learning. ...
Acknowledgments Many thanks to the reviewers for valuable feedback and suggestions. The authors benefited from discussions with the machine learning and data mining groups at Yahoo! ...
doi:10.1145/1401890.1401954
dblp:conf/kdd/MadaniH08
fatcat:wsr5kviodvhareqlycd4qguwou
Graph-based approach for airborne light detection and ranging segmentation
2017
Journal of Applied Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
A few models are clearly better than the remaining ones: random forest, SVM with Gaussian and polynomial kernels, extreme learning machine with Gaussian kernel, C5.0 and avNNet (a committee of multi-layer ...
perceptrons implemented in R with the caret package). ...
Acknowledgments We would like to acknowledge support from the Spanish Ministry of Science and Innovation (MICINN), which supported this work under projects TIN2011-22935 and TIN2012-32262. ...
doi:10.1117/1.jrs.11.015020
fatcat:6w3qqyj7vvckjkfzuulhzwojb4
« Previous
Showing results 1 — 15 out of 696 results