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09/19/2022
Toward Understanding Privileged Features Distillation in Learning-to-Rank
In learning-to-rank problems, a privileged feature is one that is availa...
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04/29/2020
DS-FACTO: Doubly Separable Factorization Machines
Factorization Machines (FM) are powerful class of models that incorporat...
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08/29/2019
A Zero Attention Model for Personalized Product Search
Product search is one of the most popular methods for people to discover...
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10/22/2018
An Efficient Bandit Algorithm for Realtime Multivariate Optimization
Optimization is commonly employed to determine the content of web pages,...
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05/31/2016
Extreme Stochastic Variational Inference: Distributed and Asynchronous
We propose extreme stochastic variational inference (ESVI), an asynchron...
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04/16/2016
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression
Scaling multinomial logistic regression to datasets with very large numb...
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11/21/2015
BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies
We propose BlackOut, an approximation algorithm to efficiently train mas...
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06/09/2015
WordRank: Learning Word Embeddings via Robust Ranking
Embedding words in a vector space has gained a lot of attention in recen...
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02/11/2014
Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data
We propose RoBiRank, a ranking algorithm that is motivated by observing ...
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02/27/2012
Efficiently Sampling Multiplicative Attribute Graphs Using a Ball-Dropping Process
We introduce a novel and efficient sampling algorithm for the Multiplica...
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10/24/2011
Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs
We describe the first sub-quadratic sampling algorithm for the Multiplic...
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09/07/2009
Lower Bounds for BMRM and Faster Rates for Training SVMs
Regularized risk minimization with the binary hinge loss and its variant...
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04/24/2008
