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Computational Linguistics
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval as statistical translation
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Cross-Language Information Retrieval
Cross-Language Information Retrieval
Modern Information Retrieval
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The Journal of Machine Learning Research
Links between perceptrons, MLPs and SVMs
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Supervised Latent Semantic Indexing for Document Categorization
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Inferring document similarity from hyperlinks
Proceedings of the 14th ACM international conference on Information and knowledge management
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
The rate adapting poisson model for information retrieval and object recognition
ICML '06 Proceedings of the 23rd international conference on Machine learning
Latent semantic analysis for multiple-type interrelated data objects
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Learning to rank: from pairwise approach to listwise approach
Proceedings of the 24th international conference on Machine learning
A support vector method for optimizing average precision
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A knowledge-based search engine powered by wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Wikipedia-Based Kernels for Text Categorization
SYNASC '07 Proceedings of the Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
A Discriminative Kernel-Based Approach to Rank Images from Text Queries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast solvers and efficient implementations for distance metric learning
Proceedings of the 25th international conference on Machine learning
Enhancing text clustering by leveraging Wikipedia semantics
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Query-drift prevention for robust query expansion
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A neural network for text representation
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
Data-aware scheduling of legacy kernels on heterogeneous platforms with distributed memory
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Active learning to maximize accuracy vs. effort in interactive information retrieval
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
A Massively Parallel, Energy Efficient Programmable Accelerator for Learning and Classification
ACM Transactions on Architecture and Code Optimization (TACO)
Extending BM25 with multiple query operators
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Methodologies for improved tag cloud generation with clustering
ICWE'12 Proceedings of the 12th international conference on Web Engineering
Low-dimensional discriminative reranking
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Metric learning for large scale image classification: generalizing to new classes at near-zero cost
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
COSMIC: middleware for high performance and reliable multiprocessing on xeon phi coprocessors
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A low rank structural large margin method for cross-modal ranking
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Cross-media semantic representation via bi-directional learning to rank
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IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In this article we present Supervised Semantic Indexing which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word content in a query-document or document-document pair to a ranking score. Like Latent Semantic Indexing (LSI), our models take account of correlations between words (synonymy, polysemy). However, unlike LSI our models are trained from a supervised signal directly on the ranking task of interest, which we argue is the reason for our superior results. As the query and target texts are modeled separately, our approach is easily generalized to different retrieval tasks, such as cross-language retrieval or online advertising placement. Dealing with models on all pairs of words features is computationally challenging. We propose several improvements to our basic model for addressing this issue, including low rank (but diagonal preserving) representations, correlated feature hashing and sparsification. We provide an empirical study of all these methods on retrieval tasks based on Wikipedia documents as well as an Internet advertisement task. We obtain state-of-the-art performance while providing realistically scalable methods.