Carlotta Domeniconi

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George Mason University

Few-Shot Partial-Label Learning

Partial-label learning (PLL) generally focuses on inducing a noise-toler...
06/02/2021 ∙ by Yunfeng Zhao, et al. ∙ 0 ∙ share

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Unsupervised Selective Manifold Regularized Matrix Factorization

Manifold regularization methods for matrix factorization rely on the clu...
10/20/2020 ∙ by Priya Mani, et al. ∙ 0 ∙ share

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Effects of Model Misspecification on Bayesian Bandits: Case Studies in UX Optimization

Bayesian bandits using Thompson Sampling have seen increasing success in...
10/07/2020 ∙ by Mack Sweeney, et al. ∙ 0 ∙ share

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Multi-typed Objects Multi-view Multi-instance Multi-label Learning

Multi-typed objects Multi-view Multi-instance Multi-label Learning (M4L)...
10/06/2020 ∙ by Yuanlin Yang, et al. ∙ 0 ∙ share

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Deep Incomplete Multi-View Multiple Clusterings

Multi-view clustering aims at exploiting information from multiple heter...
10/02/2020 ∙ by Shaowei Wei, et al. ∙ 3 ∙ share

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Attention-Aware Answers of the Crowd

Crowdsourcing is a relatively economic and efficient solution to collect...
12/24/2019 ∙ by Jingzheng Tu, et al. ∙ 1 ∙ share

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Active Multi-Label Crowd Consensus

Crowdsourcing is an economic and efficient strategy aimed at collecting ...
11/07/2019 ∙ by Jinzheng Tu, et al. ∙ 0 ∙ share

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Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection

Autoencoders, as a dimensionality reduction technique, have been recentl...
10/22/2019 ∙ by Hamed Sarvari, et al. ∙ 0 ∙ share

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Estimator Vectors: OOV Word Embeddings based on Subword and Context Clue Estimates

Semantic representations of words have been successfully extracted from ...
10/18/2019 ∙ by Raj Patel, et al. ∙ 0 ∙ share

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Cross-modal Zero-shot Hashing

Hashing has been widely studied for big data retrieval due to its low st...
08/19/2019 ∙ by Xuanwu Liu, et al. ∙ 1 ∙ share

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Weakly-paired Cross-Modal Hashing

Hashing has been widely adopted for large-scale data retrieval in many d...
05/29/2019 ∙ by Xuanwu Liu, et al. ∙ 4 ∙ share

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ActiveHNE: Active Heterogeneous Network Embedding

Heterogeneous network embedding (HNE) is a challenging task due to the d...
05/14/2019 ∙ by Xia Chen, et al. ∙ 6 ∙ share

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Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization

Multi-view Multi-instance Multi-label Learning(M3L) deals with complex o...
05/13/2019 ∙ by Yuying Xing, et al. ∙ 12 ∙ share

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Multi-View Multiple Clustering

Multiple clustering aims at exploring alternative clusterings to organiz...
05/13/2019 ∙ by Shixing Yao, et al. ∙ 4 ∙ share

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Ranking-based Deep Cross-modal Hashing

Cross-modal hashing has been receiving increasing interests for its low ...
05/11/2019 ∙ by Xuanwu Liu, et al. ∙ 1 ∙ share

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Multiple Independent Subspace Clusterings

Multiple clustering aims at discovering diverse ways of organizing data ...
05/10/2019 ∙ by Xing Wang, et al. ∙ 4 ∙ share

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Graph-based Selective Outlier Ensembles

An ensemble technique is characterized by the mechanism that generates t...
04/17/2018 ∙ by Hamed Sarvari, et al. ∙ 0 ∙ share

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Carlotta Domeniconi

Featured Co-authors

Jun Wang

Xiangliang Zhang

Lei Liu

Xing Wang

Zhao Li

Lizhen Cui

Guoxian Yu

Yazhou Ren

Igor Griva

Giovanni Stilo

Xia Chen

Few-Shot Partial-Label Learning

Unsupervised Selective Manifold Regularized Matrix Factorization

Effects of Model Misspecification on Bayesian Bandits: Case Studies in UX Optimization

Multi-typed Objects Multi-view Multi-instance Multi-label Learning

Deep Incomplete Multi-View Multiple Clusterings

Attention-Aware Answers of the Crowd

Active Multi-Label Crowd Consensus

Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection

Estimator Vectors: OOV Word Embeddings based on Subword and Context Clue Estimates

Cross-modal Zero-shot Hashing

Weakly-paired Cross-Modal Hashing

ActiveHNE: Active Heterogeneous Network Embedding

Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization

Multi-View Multiple Clustering

Ranking-based Deep Cross-modal Hashing

Multiple Independent Subspace Clusterings

Graph-based Selective Outlier Ensembles