Akshay Soni | DeepAI

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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...

11 Kunal Dahiya, et al. ∙

∙ 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 ...

5 Junhan Yang, et al. ∙

∙ 02/18/2021

Multi-Interest-Aware User Modeling for Large-Scale Sequential Recommendations

Precise user modeling is critical for online personalized recommendation...

0 Jianxun Lian, et al. ∙

∙ 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...

0 Iyad Batal, et al. ∙

∙ 06/21/2018

Towards Automated Single Channel Source Separation using Neural Networks

Many applications of single channel source separation (SCSS) including a...

0 Arpita Gang, et al. ∙

∙ 04/24/2018

On Learning Sparsely Used Dictionaries from Incomplete Samples

Most existing algorithms for dictionary learning assume that all entries...

0 Thanh V. Nguyen, et al. ∙

∙ 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...

0 Sheng Chen, et al. ∙

∙ 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...

0 Jeya Balaji Balasubramanian, et al. ∙

∙ 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...

0 Swayambhoo Jain, et al. ∙

∙ 02/16/2017

RIPML: A Restricted Isometry Property based Approach to Multilabel Learning

The multilabel learning problem with large number of labels, features, a...

0 Akshay Soni, et al. ∙

∙ 09/13/2016

Noisy Inductive Matrix Completion Under Sparse Factor Models

Inductive Matrix Completion (IMC) is an important class of matrix comple...

0 Akshay Soni, et al. ∙

∙ 11/02/2014

Noisy Matrix Completion under Sparse Factor Models

This paper examines a general class of noisy matrix completion tasks whe...

0 Akshay Soni, et al. ∙

∙ 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...

0 Swayambhoo Jain, et al. ∙

∙ 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...

0 Akshay Soni, et al. ∙

∙ 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...

0 Akshay Soni, et al. ∙

∙ 11/29/2011

Efficient Adaptive Compressive Sensing Using Sparse Hierarchical Learned Dictionaries

Recent breakthrough results in compressed sensing (CS) have established ...

0 Akshay Soni, et al. ∙

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