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07/10/2022
NGAME: Negative Mining-aware Mini-batching for Extreme Classification
Extreme Classification (XC) seeks to tag data points with the most relev...
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04/22/2021
Hybrid Encoder: Towards Efficient and Precise Native AdsRecommendation via Hybrid Transformer Encoding Networks
Transformer encoding networks have been proved to be a powerful tool of ...
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02/18/2021
Multi-Interest-Aware User Modeling for Large-Scale Sequential Recommendations
Precise user modeling is critical for online personalized recommendation...
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12/27/2020
Multi-Channel Sequential Behavior Networks for User Modeling in Online Advertising
Multiple content providers rely on native advertisement for revenue by p...
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06/21/2018
Towards Automated Single Channel Source Separation using Neural Networks
Many applications of single channel source separation (SCSS) including a...
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04/24/2018
On Learning Sparsely Used Dictionaries from Incomplete Samples
Most existing algorithms for dictionary learning assume that all entries...
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07/14/2017
DocTag2Vec: An Embedding Based Multi-label Learning Approach for Document Tagging
Tagging news articles or blog posts with relevant tags from a collection...
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05/16/2017
Online Article Ranking as a Constrained, Dynamic, Multi-Objective Optimization Problem
The content ranking problem in a social news website, is typically a fun...
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02/24/2017
Rank-to-engage: New Listwise Approaches to Maximize Engagement
For many internet businesses, presenting a given list of items in an ord...
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02/16/2017
RIPML: A Restricted Isometry Property based Approach to Multilabel Learning
The multilabel learning problem with large number of labels, features, a...
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09/13/2016
Noisy Inductive Matrix Completion Under Sparse Factor Models
Inductive Matrix Completion (IMC) is an important class of matrix comple...
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11/02/2014
Noisy Matrix Completion under Sparse Factor Models
This paper examines a general class of noisy matrix completion tasks whe...
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11/21/2013
Compressive Measurement Designs for Estimating Structured Signals in Structured Clutter: A Bayesian Experimental Design Approach
This work considers an estimation task in compressive sensing, where the...
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06/18/2013
On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy Linear Measurements
Recent breakthrough results in compressive sensing (CS) have established...
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10/09/2012
Level Set Estimation from Compressive Measurements using Box Constrained Total Variation Regularization
Estimating the level set of a signal from measurements is a task that ar...
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11/29/2011
